Marburg virus (MARV) and Ebola virus (EBOV), members of the family Filoviridae, represent a significant challenge to global public health. Currently, no licensed therapies exist to treat filovirus infections, which cause up to 90% mortality in human cases. To facilitate development of antivirals against these viruses, we established two distinct screening platforms based on MARV and EBOV reversegenetics systems that express secreted Gaussia luciferase (gLuc). The first platform is a mini-genome replicon to screen viral replication inhibitors using gLuc quantification in a BSL-2 setting. The second platform is complementary to the first and expresses gLuc as a reporter gene product encoded in recombinant infectious MARV and EBOV, thereby allowing for rapid quantification of viral growth during treatment with antiviral compounds. We characterized these viruses by comparing luciferase activity to virus production, and validated luciferase activity as an authentic real-time measure of viral growth. As proof of concept, we adapt both mini-genome and infectious virus platforms to high-throughput formats, and demonstrate efficacy of several antiviral compounds. We anticipate that both approaches will prove highly useful in the development of anti-filovirus therapies, as well as in basic research on the filovirus life cycle.

Reversegenetics approaches are indispensable tools for proof of concepts in virus replication and pathogenesis. For negative strand RNA viruses (NSVs) the limited number of infectious cDNA clones represents a bottleneck as clones are often generated from cell culture adapted or attenuated viruses, with limited potential for pathogenesis research. We developed a system in which cDNA copies of complete NSV genomes were directly cloned into reversegenetics vectors by linear-to-linear RedE/T recombination. Rapid cloning of multiple rabies virus (RABV) full length genomes and identification of clones identical to field virus consensus sequence confirmed the approache’s reliability. Recombinant viruses were recovered from field virus cDNA clones. Similar growth kinetics of parental and recombinant viruses, preservation of field virus characters in cell type specific replication and virulence in the mouse model were confirmed. Reduced titers after reporter gene insertion indicated that the low level of field virus replication is affected by gene insertions. The flexibility of the strategy was demonstrated by cloning multiple copies of an orthobunyavirus L genome segment. This important step in reversegenetics technology development opens novel avenues for the analysis of virus variability combined with phenotypical characterization of recombinant viruses at a clonal level. PMID:27046474

Reversegenetics approaches are indispensable tools for proof of concepts in virus replication and pathogenesis. For negative strand RNA viruses (NSVs) the limited number of infectious cDNA clones represents a bottleneck as clones are often generated from cell culture adapted or attenuated viruses, with limited potential for pathogenesis research. We developed a system in which cDNA copies of complete NSV genomes were directly cloned into reversegenetics vectors by linear-to-linear RedE/T recombination. Rapid cloning of multiple rabies virus (RABV) full length genomes and identification of clones identical to field virus consensus sequence confirmed the approache's reliability. Recombinant viruses were recovered from field virus cDNA clones. Similar growth kinetics of parental and recombinant viruses, preservation of field virus characters in cell type specific replication and virulence in the mouse model were confirmed. Reduced titers after reporter gene insertion indicated that the low level of field virus replication is affected by gene insertions. The flexibility of the strategy was demonstrated by cloning multiple copies of an orthobunyavirus L genome segment. This important step in reversegenetics technology development opens novel avenues for the analysis of virus variability combined with phenotypical characterization of recombinant viruses at a clonal level.

Comprehensive delineation of complex cellular networks requires high-throughput interrogation of genetic interactions. To address this challenge, we describe the development of a multiplex combinatorial strategy to assess pairwise genetic interactions using CRISPR-Cas9 genome editing and next-generation sequencing. We characterize the performance of combinatorial genome editing and analysis using different promoter and gRNA designs and identified regions of the chimeric RNA that are compatible with next-generation sequencing preparation and quantification. This approach is an important step towards elucidating genetic networks relevant to human diseases and the development of more efficient Cas9-based therapeutics. PMID:27936040

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize

The biotechnological advances of the last decade have confronted us with an explosion of genetics, genomics, transcriptomics, proteomics, and metabolomics data. These data need to be organized and structured before they may provide a coherent biological picture. To accomplish this formidable task, the availability of an accurate map of the physical interactions in the cell that are responsible for cellular behavior and function would be exceedingly helpful, as these data are ultimately the result of such molecular interactions. However, all we have at this time is, at best, a fragmentary and only partially correct representation of the interactions between genes, their byproducts, and other cellular entities. If we want to succeed in our quest for understanding the biological whole as more than the sum of the individual parts, we need to build more comprehensive and cell-context-specific maps of the biological interaction networks. DREAM, the Dialogue on Reverse Engineering Assessment and Methods, is fostering a concerted effort by computational and experimental biologists to understand the limitations and to enhance the strengths of the efforts to reverse engineer cellular networks from high-throughput data. In this chapter we will discuss the salient arguments of the first DREAM conference. We will highlight both the state of the art in the field of reverse engineering as well as some of its challenges and opportunities.

The present invention provides novel recombinant baculovirus expression systems for expressing foreign genetic material in a host cell. Such expression systems are readily adapted to an automated method for expression foreign genetic material in a highthroughput manner. In other aspects, the present invention features a novel automated method for determining the function of foreign genetic material by transfecting the same into a host by way of the recombinant baculovirus expression systems according to the present invention.

The last decade has seen considerable advances in our understanding of the genetic basis of skin disease, as a consequence of highthroughput sequencing technologies including next generation sequencing and whole exome sequencing. We have now determined the genes underlying several monogenic diseases, such as harlequin ichthyosis, Olmsted syndrome, and exfoliative ichthyosis, which have provided unique insights into the structure and function of the skin. In addition, through genome wide association studies we now have an understanding of how low penetrance variants contribute to inflammatory skin diseases such as psoriasis vulgaris and atopic dermatitis, and how they contribute to underlying pathophysiological disease processes. In this review we discuss strategies used to unravel the genes underlying both monogenic and complex trait skin diseases in the last 10 years and the implications on mechanistic studies, diagnostics, and therapeutics. PMID:25093584

Vaccine reverse engineering is emerging as an important approach to vaccine antigen identification, recently focusing mainly on structural characterization of interactions between neutralizing monoclonal antibodies (mAbs) and antigens. Using mAbs that bind unknown antigen structures, we sought to probe the intrinsic features of antibody antigen-binding sites with a high complexity peptide library, aiming to identify conformationally optimized mimotope antigens that capture mAb-specific epitopes. Using a highthroughput sequencing-enhanced messenger ribonucleic acid (mRNA) display approach, we identified high affinity binding peptides for a hepatitis C virus neutralizing mAb. Immunization with the selected peptides induced neutralizing activity similar to that of the original mAb. Antibodies elicited by the most commonly selected peptides were predominantly against specific epitopes. Thus, using mRNA display to interrogate mAbs permits high resolution identification of functional peptide antigens that direct targeted immune responses, supporting its use in vaccine reverse engineering for pathogens against which potent neutralizing mAbs are available. Research in Context We used a large number of randomly produced small proteins (“peptides”) to identify peptides containing specific protein sequences that bind efficiently to an antibody that can prevent hepatitis C virus infection in cell culture. After the identified peptides were injected into mice, the mice produced their own antibodies with characteristics similar to the original antibody. This approach can provide previously unavailable information about antibody binding and could also be useful in developing new vaccines. PMID:26425692

Food security has emerged as an urgent concern because of the rising world population. To meet the food demands of the near future, it is required to improve the productivity of various crops, not just of staple food crops. The genetic diversity among plant populations in a given species allows the plants to adapt to various environmental conditions. Such diversity could therefore yield valuable traits that could overcome the food-security challenges. To explore genetic diversity comprehensively and to rapidly identify useful genes and/or allele, advanced high-throughput sequencing techniques, also called next-generation sequencing (NGS) technologies, have been developed. These provide practical solutions to the challenges in crop genomics. Here, we review various sources of genetic diversity in plants, newly developed genetic diversity-mining tools synergized with NGS techniques, and related genetic approaches such as quantitative trait locus analysis and genome-wide association study. PMID:27499684

Food security has emerged as an urgent concern because of the rising world population. To meet the food demands of the near future, it is required to improve the productivity of various crops, not just of staple food crops. The genetic diversity among plant populations in a given species allows the plants to adapt to various environmental conditions. Such diversity could therefore yield valuable traits that could overcome the food-security challenges. To explore genetic diversity comprehensively and to rapidly identify useful genes and/or allele, advanced high-throughput sequencing techniques, also called next-generation sequencing (NGS) technologies, have been developed. These provide practical solutions to the challenges in crop genomics. Here, we review various sources of genetic diversity in plants, newly developed genetic diversity-mining tools synergized with NGS techniques, and related genetic approaches such as quantitative trait locus analysis and genome-wide association study.

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction.

Traditional gene mapping using forward genetic approaches is conducted primarily through construction of a genetic linkage map, the process of which is tedious and time-consuming, and often results in low accuracy of mapping and large mapping intervals. With the rapid development of high-throughput sequencing technology and decreasing cost of sequencing, a variety of simple and quick methods of gene mapping through sequencing have been developed, including direct sequencing of the mutant genome, sequencing of selective mutant DNA pooling, genetic map construction through sequencing of individuals in population, as well as sequencing of transcriptome and partial genome. These methods can be used to identify mutations at the nucleotide level and has been applied in complex genetic background. Recent reports have shown that sequencing mapping could be even done without the reference of genome sequence, hybridization, and genetic linkage information, which made it possible to perform forward genetic study in many non-model species. In this review, we summarized these new technologies and their application in gene mapping.

Robust methods for genetic analysis are required for efficient exploitation of the constantly accumulating genetic information. We describe a closed-tube genotyping method suitable for high-throughput screening of genetic markers. The method is based on allele-specific probes labeled with an environment-sensitive lanthanide chelate, the fluorescence intensity of which is significantly increased upon PCR amplification of a complementary target. Genomic DNA samples were analyzed in an insulin gene single nucleotide polymorphism (SNP) assay using universal amplification primers and probes that recognized the two different alleles. The feasibility of dry reagent based all-in-one PCR assays was tested using another diabetes-related genetic marker, human leukocyte antigen DQB1 allele *0302 as a model analyte in a dual-color, closed-tube end-point assay. There was a 100% correlation between the novel SNP assay and a conventional PCR restriction fragment length polymorphism assay. It was also demonstrated that using real-time monitoring, accurate genotyping results can be obtained despite strongly cross-reacting probes, minimizing the time and effort needed for optimization of probe sequence. Throughput can be maximized by using predried PCR mixtures that are stable for at least 6 months. This homogenous, all-in-one dry reagent assay chemistry permits cost-effective genetic screening on a large scale.

Background Gene expression profiling and other genome-scale measurement technologies provide comprehensive information about molecular changes resulting from a chemical or genetic perturbation, or disease state. A critical challenge is the development of methods to interpret these large-scale data sets to identify specific biological mechanisms that can provide experimentally verifiable hypotheses and lead to the understanding of disease and drug action. Results We present a detailed description of Reverse Causal Reasoning (RCR), a reverse engineering methodology to infer mechanistic hypotheses from molecular profiling data. This methodology requires prior knowledge in the form of small networks that causally link a key upstream controller node representing a biological mechanism to downstream measurable quantities. These small directed networks are generated from a knowledge base of literature-curated qualitative biological cause-and-effect relationships expressed as a network. The small mechanism networks are evaluated as hypotheses to explain observed differential measurements. We provide a simple implementation of this methodology, Whistle, specifically geared towards the analysis of gene expression data and using prior knowledge expressed in Biological Expression Language (BEL). We present the Whistle analyses for three transcriptomic data sets using a publically available knowledge base. The mechanisms inferred by Whistle are consistent with the expected biology for each data set. Conclusions Reverse Causal Reasoning yields mechanistic insights to the interpretation of gene expression profiling data that are distinct from and complementary to the results of analyses using ontology or pathway gene sets. This reverse engineering algorithm provides an evidence-driven approach to the development of models of disease, drug action, and drug toxicity. PMID:24266983

The simplicity of the CRISPR/Cas9 system of genome engineering has opened up the possibility of performing genome-wide targeted mutagenesis in cell lines, enabling screening for cellular phenotypes resulting from genetic aberrations. Drosophila cells have proven to be highly effective in identifying genes involved in cellular processes through similar screens using partial knockdown by RNAi. This is in part due to the lower degree of redundancy between genes in this organism, whilst still maintaining highly conserved gene networks and orthologs of many human disease-causing genes. The ability of CRISPR to generate genetic loss of function mutations not only increases the magnitude of any effect over currently employed RNAi techniques, but allows analysis over longer periods of time which can be critical for certain phenotypes. In this study, we have designed and built a genome-wide CRISPR library covering 13,501 genes, among which 8989 genes are targeted by three or more independent single guide RNAs (sgRNAs). Moreover, we describe strategies to monitor the population of guide RNAs by highthroughput sequencing (HTS). We hope that this library will provide an invaluable resource for the community to screen loss of function mutations for cellular phenotypes, and as a source of guide RNA designs for future studies. PMID:26165496

The simplicity of the CRISPR/Cas9 system of genome engineering has opened up the possibility of performing genome-wide targeted mutagenesis in cell lines, enabling screening for cellular phenotypes resulting from genetic aberrations. Drosophila cells have proven to be highly effective in identifying genes involved in cellular processes through similar screens using partial knockdown by RNAi. This is in part due to the lower degree of redundancy between genes in this organism, whilst still maintaining highly conserved gene networks and orthologs of many human disease-causing genes. The ability of CRISPR to generate genetic loss of function mutations not only increases the magnitude of any effect over currently employed RNAi techniques, but allows analysis over longer periods of time which can be critical for certain phenotypes. In this study, we have designed and built a genome-wide CRISPR library covering 13,501 genes, among which 8989 genes are targeted by three or more independent single guide RNAs (sgRNAs). Moreover, we describe strategies to monitor the population of guide RNAs by highthroughput sequencing (HTS). We hope that this library will provide an invaluable resource for the community to screen loss of function mutations for cellular phenotypes, and as a source of guide RNA designs for future studies.

The recent development of a high-throughput single-cell assay technique enables the screening of novel enzymes based on functional activities from a large-scale metagenomic library(1). We previously proposed a genetic enzyme screening system (GESS) that uses dimethylphenol regulator activated by phenol or p-nitrophenol. Since a vast amount of natural enzymatic reactions produce these phenolic compounds from phenol deriving substrates, this single genetic screening system can be theoretically applied to screen over 200 different enzymes in the BRENDA database. Despite the general applicability of GESS, applying the screening process requires a specific procedure to reach the maximum flow cytometry signals. Here, we detail the developed screening process, which includes metagenome preprocessing with GESS and the operation of a flow cytometry sorter. Three different phenolic substrates (p-nitrophenyl acetate, p-nitrophenyl-β-D-cellobioside, and phenyl phosphate) with GESS were used to screen and to identify three different enzymes (lipase, cellulase, and alkaline phosphatase), respectively. The selected metagenomic enzyme activities were confirmed only with the flow cytometry but DNA sequencing and diverse in vitro analysis can be used for further gene identification.

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits. PMID:25295980

Therapeutic treatment of spinal cord injuries, brain trauma, stroke, and neurodegenerative diseases will greatly benefit from the discovery of compounds that enhance neuronal regeneration following injury. We previously demonstrated the use of femtosecond laser microsurgery to induce precise and reproducible neural injury in C. elegans, and have developed microfluidic on-chip technologies that allow automated and rapid manipulation, orientation, and non-invasive immobilization of animals for sub-cellular resolution two-photon imaging and femtosecond-laser nanosurgery. These technologies include microfluidic whole-animal sorters, as well as integrated chips containing multiple addressable incubation chambers for exposure of individual animals to compounds and sub-cellular time-lapse imaging of hundreds of animals on a single chip. Our technologies can be used for a variety of highly sophisticated in vivo high-throughput compound and genetic screens, and we performed the first in vivo screen in C. elegans for compounds enhancing neuronal regrowth following femtosecond microsurgery. The compounds identified interact with a wide variety of cellular targets, such as cytoskeletal components, vesicle trafficking, and protein kinases that enhance neuronal regeneration.

Identifying genes causing non-syndromic hearing loss has been challenging using traditional approaches. We describe the impact that high-throughput sequencing approaches are having in discovery of genes related to hearing loss and the implications for clinical diagnosis. PMID:22647651

Next-generation RNA-sequencing (RNA-seq) has revolutionized transcriptome profiling, gene expression analysis, and RNA-based diagnostics. Here, we developed a new RNA-seq method that exploits thermostable group II intron reverse transcriptases (TGIRTs) and used it to profile human plasma RNAs. TGIRTs have higher thermostability, processivity, and fidelity than conventional reverse transcriptases, plus a novel template-switching activity that can efficiently attach RNA-seq adapters to target RNA sequences without RNA ligation. The new TGIRT-seq method enabled construction of RNA-seq libraries from <1 ng of plasma RNA in <5 h. TGIRT-seq of RNA in 1-mL plasma samples from a healthy individual revealed RNA fragments mapping to a diverse population of protein-coding gene and long ncRNAs, which are enriched in intron and antisense sequences, as well as nearly all known classes of small ncRNAs, some of which have never before been seen in plasma. Surprisingly, many of the small ncRNA species were present as full-length transcripts, suggesting that they are protected from plasma RNases in ribonucleoprotein (RNP) complexes and/or exosomes. This TGIRT-seq method is readily adaptable for profiling of whole-cell, exosomal, and miRNAs, and for related procedures, such as HITS-CLIP and ribosome profiling.

Measuring forces applied by multi-cellular organisms is valuable in investigating biomechanics of their locomotion. Several technologies have been developed to measure such forces, for example, strain gauges, micro-machined sensors, and calibrated cantilevers. We introduce an innovative combination of techniques as a highthroughput screening tool to assess forces applied by multiple genetic model organisms. First, we fabricated colored Polydimethylsiloxane (PDMS) micropillars where the color enhances contrast making it easier to detect and track pillar displacement driven by the organism. Second, we developed a semi-automated graphical user interface to analyze the images for pillar displacement, thus reducing the analysis time for each animal to minutes. The addition of color reduced the Young's modulus of PDMS. Therefore, the dye-PDMS composite was characterized using Yeoh's hyperelastic model and the pillars were calibrated using a silicon based force sensor. We used our device to measure forces exerted by wild type and mutant Caenorhabditis elegans moving on an agarose surface. Wild type C. elegans exert an average force of ∼1 μN on an individual pillar and a total average force of ∼7.68 μN. We show that the middle of C. elegans exerts more force than its extremities. We find that C. elegans mutants with defective body wall muscles apply significantly lower force on individual pillars, while mutants defective in sensing externally applied mechanical forces still apply the same average force per pillar compared to wild type animals. Average forces applied per pillar are independent of the length, diameter, or cuticle stiffness of the animal. We also used the device to measure, for the first time, forces applied by Drosophila melanogaster larvae. Peristaltic waves occurred at 0.4 Hz applying an average force of ∼1.58 μN on a single pillar. Our colored microfluidic device along with its displacement tracking software allows us to measure forces

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based highthroughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection.

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based highthroughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection. PMID:25556930

High-throughput screening (HTS) is a powerful approach to drug discovery, but many lead compounds are found to be unsuitable for use in vivo after initial screening. Screening in small animals like C. elegans can help avoid these problems, but this system has been limited to screens with low-throughput or no specific molecular target. We report the first in vivo 1536-well plate assay for a specific genetic pathway in C. elegans. Our assay measures induction of a gene regulated by SKN-1, a master regulator of detoxification genes. SKN-1 inhibitors will be used to study and potentially reverse multidrug resistance in parasitic nematodes. Screens of two small commercial libraries and the full Molecular Libraries Small Molecule Repository (MLSMR) of ∼364,000 compounds validate our platform for ultra HTS. Our platform overcomes current limitations of many whole-animal screens and can be widely adopted for other inducible genetic pathways in nematodes and humans. PMID:23637990

In the post-genomic era, academic and biotechnological research is increasingly shifting its attention from single proteins to the analysis of complex protein networks. This change in experimental design requires the use of simple and experimentally tractable organisms, such as the unicellular eukaryote Saccharomyces cerevisiae, and a range of new high-throughput techniques. The Gateway system has emerged as a powerful high-throughput cloning method that allows for the in vitro recombination of DNA with high speed, accuracy and reliability. Two Gateway-based libraries of overexpression plasmids containing the entire complement of yeast open reading frames (ORFs) have recently been completed. In order to make use of these powerful resources, we adapted the widely used pRS series of yeast shuttle vectors for use in Gateway-based cloning. The resulting suite of 288 yeast Gateway vectors is based upon the two commonly used GPD and GAL1 promoter expression systems that enable expression of ORFs, either constitutively or under galactose-inducible conditions. In addition, proteins of interest can be fused to a choice of frequently used N- or C-terminal tags, such as EGFP, ECFP, EYFP, Cerulean, monomeric DsRed, HA or TAP. We have made this yeast Gateway vector kit available to the research community via the non-profit Addgene Plasmid Repository (http://www.addgene.org/yeast_gateway).

With increasing demand for novel traits in crop breeding, the plant research community faces the challenge of quantitatively analyzing the structure and function of large numbers of plants. A clear goal of high-throughput phenotyping is to bridge the gap between genomics and phenomics. In this study, we quantified 106 traits from a maize (Zea mays) recombinant inbred line population (n = 167) across 16 developmental stages using the automatic phenotyping platform. Quantitative trait locus (QTL) mapping with a high-density genetic linkage map, including 2,496 recombinant bins, was used to uncover the genetic basis of these complex agronomic traits, and 988 QTLs have been identified for all investigated traits, including three QTL hotspots. Biomass accumulation and final yield were predicted using a combination of dissected traits in the early growth stage. These results reveal the dynamic genetic architecture of maize plant growth and enhance ideotype-based maize breeding and prediction. PMID:28153923

High-throughput experimental methodologies are capable of synthesizing, screening and characterizing vast arrays of combinatorial material libraries at a very rapid rate. These methodologies strategically employ tiered screening wherein the number of compositions screened decreases as the complexity, and very often the scientific information obtained from a screening experiment, increases. The algorithm used for down-selection of samples from higher throughput screening experiment to a lower throughput screening experiment is vital in achieving information-rich experimental materials genomes. The fundamental science of material discovery lies in the establishment of composition-structure-property relationships, motivating the development of advanced down-selection algorithms which consider the information value of the selected compositions, as opposed to simply selecting the best performing compositions from a highthroughput experiment. Identification of property fields (composition regions with distinct composition-property relationships) in highthroughput data enables down-selection algorithms to employ advanced selection strategies, such as the selection of representative compositions from each field or selection of compositions that span the composition space of the highest performing field. Such strategies would greatly enhance the generation of data-driven discoveries. We introduce an informatics-based clustering of composition-property functional relationships using a combination of information theory and multitree genetic programming concepts for identification of property fields in a composition library. We demonstrate our approach using a complex synthetic composition-property map for a 5 at. % step ternary library consisting of four distinct property fields and finally explore the application of this methodology for capturing relationships between composition and catalytic activity for the oxygen evolution reaction for 5429 catalyst compositions in a

Helicobacter pylori (H. pylori) infection is closely related to various gastroduodenal diseases. Virulence factors and bacterial load of H. pylori are associated with clinical outcomes, and drug-resistance severely impacts the clinical efficacy of eradication treatment. Existing detection methods are low-throughput, time-consuming and labor intensive. Therefore, a rapid and high-throughput method is needed for clinical diagnosis, treatment, and monitoring for H. pylori. High-throughput Multiplex Genetic Detection System (HMGS) assay was established to simultaneously detect and analyze a set of genes for H. pylori identification, quantification, virulence, and drug resistance by optimizing the singlet-PCR and multiple primers assay. Twenty-one pairs of chimeric primers consisted of conserved and specific gene sequences of H. pylori tagged with universal sequence at the 5′ end were designed. Singlet-PCR assay and multiple primers assay were developed to optimize the HMGS. The specificity of HMGS assay was evaluated using standard H. pylori strains and bacterial controls. Six clinical isolates with known genetic background of target genes were detected to assess the accuracy of HMGS assay. Artificial mixed pathogen DNA templates were used to evaluate the ability to distinguish mixed infections using HMGS assay. Furthermore, gastric biopsy specimens with corresponding isolated strains were used to assess the capability of HMGS assay in detecting biopsy specimens directly. HMGS assay was specific for H. pylori identification. HMGS assay for H. pylori target genes detection were completely consistent with the corresponding genetic background. Mixed infection with different drug-resistant isolates of H. pylori could be distinguished by HMGS assay. HMGS assay could efficiently diagnose H. pylori infection in gastric biopsy specimens directly. HMGS assay is a rapid and highthroughput method for the simultaneous identification and quantification of H. pylori, analysis of

Meiotic recombination is initiated by the formation of numerous DNA double-strand breaks (DSBs) catalysed by the widely conserved Spo11 protein. In Saccharomyces cerevisiae, Spo11 requires nine other proteins for meiotic DSB formation; however, unlike Spo11, few of these are conserved across kingdoms. In order to investigate this recombination step in higher eukaryotes, we took advantage of a high-throughput meiotic mutant screen carried out in the model plant Arabidopsis thaliana. A collection of 55,000 mutant lines was screened, and spo11-like mutations, characterised by a drastic decrease in chiasma formation at metaphase I associated with an absence of synapsis at prophase, were selected. This screen led to the identification of two populations of mutants classified according to their recombination defects: mutants that repair meiotic DSBs using the sister chromatid such as Atdmc1 or mutants that are unable to make DSBs like Atspo11-1. We found that in Arabidopsis thaliana at least four proteins are necessary for driving meiotic DSB repair via the homologous chromosomes. These include the previously characterised DMC1 and the Hop1-related ASY1 proteins, but also the meiotic specific cyclin SDS as well as the Hop2 Arabidopsis homologue AHP2. Analysing the mutants defective in DSB formation, we identified the previously characterised AtSPO11-1, AtSPO11-2, and AtPRD1 as well as two new genes, AtPRD2 and AtPRD3. Our data thus increase the number of proteins necessary for DSB formation in Arabidopsis thaliana to five. Unlike SPO11 and (to a minor extent) PRD1, these two new proteins are poorly conserved among species, suggesting that the DSB formation mechanism, but not its regulation, is conserved among eukaryotes.

The genetically-modified binding proteins calmodulin, the phosphate binding protein, the sulfate binding protein, and the galactose/glucose binding protein have been successfully employed as biosensing elements for the detection of phenothiazines, phosphate, sulfate, and glucose, respectively. Mutant proteins containing unique cysteine residues were utilized in the site-specific labeling of environment-sensitive fluorescent probes. Changes in the environment of the probes upon ligand-induced conformational changes of the proteins result in changes in fluorescence intensity.

Systemic acquired resistance (SAR) is a defense mechanism induced in the distal parts of plants after primary infection. It confers long-lasting protection against a broad spectrum of microbial pathogens. Lack of high-throughput assays has hampered the forward genetic analysis of SAR. Here, we report the development of an easy and efficient assay for SAR and its application in a forward genetic screen for SAR-deficient mutants in Arabidopsis (Arabidopsis thaliana). Using the new assay for SAR, we identified six flavin-dependent monooxygenase1, four AGD2-like defense response protein1, three salicylic acid induction-deficient2, one phytoalexin deficient4, and one avrPphB-susceptible3 alleles as well as a gain-of-function mutant of CALMODULIN-BINDING TRANSCRIPTION ACTIVATOR3 designated camta3-3D. Like transgenic plants overexpressing CAMTA3, camta3-3D mutant plants exhibit compromised SAR and enhanced susceptibility to virulent pathogens, suggesting that CAMTA3 is a critical regulator of both basal resistance and SAR.

Substantial intrastrain variation at the nucleotide level complicates molecular and genetic studies in zebrafish, such as the use of CRISPRs or morpholinos to inactivate genes. In the absence of robust inbred zebrafish lines, we generated NHGRI-1, a healthy and fecund strain derived from founder parents we sequenced to a depth of ∼50×. Within this strain, we have identified the majority of the genome that matches the reference sequence and documented most of the variants. This strain has utility for many reasons, but in particular it will be useful for any researcher who needs to know the exact sequence (with all variants) of a particular genomic region or who wants to be able to robustly map sequences back to a genome with all possible variants defined.

Banana (Musa spp.) is an important staple food as well as cash crop in tropical and subtropical countries. Various bacterial, fungal, and viral diseases and pests such as nematodes are major constraints in its production and are currently destabilizing the banana production in sub-Saharan Africa. Genetic engineering is a complementary option used for incorporating useful traits in banana to bypass the long generation time, polyploidy, and sterility of most of the cultivated varieties. A robust transformation protocol for farmer preferred varieties is crucial for banana genomics and improvement. A robust and reproducible system for genetic transformation of banana using embryogenic cell suspensions (ECS) has been developed in this study. Two different types of explants (immature male flowers and multiple buds) were tested for their ability to develop ECS in several varieties of banana locally grown in Africa. ECS of banana varieties "Cavendish Williams" and "Gros Michel" were developed using multiple buds, whereas ECS of "Sukali Ndiizi" was developed using immature male flowers. Regeneration efficiency of ECS was about 20,000-50,000 plantlets per ml of settled cell volume (SCV) depending on variety. ECS of three different varieties were transformed through Agrobacterium-mediated transformation using gusA reporter gene and 20-70 independent transgenic events per ml SCV of ECS were regenerated on selective medium. The presence and integration of gusA gene in transgenic plants was confirmed by PCR, dot blot, and Southern blot analysis and expression by histochemical GUS assays. The robust transformation platform was successfully used to generate hundreds of transgenic lines with disease resistance. Such a platform will facilitate the transfer of technologies to national agricultural research systems (NARS) in Africa.

Banana (Musa spp.) is an important staple food as well as cash crop in tropical and subtropical countries. Various bacterial, fungal, and viral diseases and pests such as nematodes are major constraints in its production and are currently destabilizing the banana production in sub-Saharan Africa. Genetic engineering is a complementary option used for incorporating useful traits in banana to bypass the long generation time, polyploidy, and sterility of most of the cultivated varieties. A robust transformation protocol for farmer preferred varieties is crucial for banana genomics and improvement. A robust and reproducible system for genetic transformation of banana using embryogenic cell suspensions (ECS) has been developed in this study. Two different types of explants (immature male flowers and multiple buds) were tested for their ability to develop ECS in several varieties of banana locally grown in Africa. ECS of banana varieties “Cavendish Williams” and “Gros Michel” were developed using multiple buds, whereas ECS of “Sukali Ndiizi” was developed using immature male flowers. Regeneration efficiency of ECS was about 20,000–50,000 plantlets per ml of settled cell volume (SCV) depending on variety. ECS of three different varieties were transformed through Agrobacterium-mediated transformation using gusA reporter gene and 20–70 independent transgenic events per ml SCV of ECS were regenerated on selective medium. The presence and integration of gusA gene in transgenic plants was confirmed by PCR, dot blot, and Southern blot analysis and expression by histochemical GUS assays. The robust transformation platform was successfully used to generate hundreds of transgenic lines with disease resistance. Such a platform will facilitate the transfer of technologies to national agricultural research systems (NARS) in Africa. PMID:26635849

The monitoring of genetically modified organisms (GMOs) is a primary step of GMO regulation. However, there is presently a lack of effective and high-throughput methodologies for specifically and sensitively monitoring most of the commercialized GMOs. Herein, we developed a multiplex amplification on a chip with readout on an oligo microarray (MACRO) system specifically for convenient GMO monitoring. This system is composed of a microchip for multiplex amplification and an oligo microarray for the readout of multiple amplicons, containing a total of 91 targets (18 universal elements, 20 exogenous genes, 45 events, and 8 endogenous reference genes) that covers 97.1% of all GM events that have been commercialized up to 2012. We demonstrate that the specificity of MACRO is ~100%, with a limit of detection (LOD) that is suitable for real-world applications. Moreover, the results obtained of simulated complex samples and blind samples with MACRO were 100% consistent with expectations and the results of independently performed real-time PCRs, respectively. Thus, we believe MACRO is the first system that can be applied for effectively monitoring the majority of the commercialized GMOs in a single test.

Fusarium oxysporum f. sp. cubense (Foc) is responsible for fusarium wilt of bananas. The pathogen consists of several variants that are divided into three races and 21 vegetative compatibility groups (VCGs). Several DNA-based techniques have previously been used to analyse the worldwide population of Foc, sometimes yielding results that were not always consistent. In this study, the high-resolution genotyping method of AFLP is introduced as a potentially effective molecular tool to investigate diversity in Foc at a genome-wide level. The population selected for this study included Foc isolates representing different VCGs and races, isolates of F. oxysporum f. sp. dianthi, a putatively non-pathogenic biological control strain F. oxysporum (Fo47), and F. circinatum. High-throughput AFLP analysis was attained using five different infrared dye-labelled primer combinations using a two-dye model 4200s LI-COR automated DNA analyser. An average of approx. 100 polymorphic loci were scored for each primer pair using the SAGA(MX) automated AFLP analysis software. Data generated from five primer pair combinations were combined and subjected to distance analysis, which included the use of neighbour-joining and a bootstrap of 1000 replicates. A tree inferred from AFLP distance analysis revealed the polyphyletic nature of the Foc isolates, and seven genotypic groups could be identified. The results indicate that AFLP is a powerful tool to perform detailed analysis of genetic diversity in the banana pathogen Foc.

The Saccharomyces cerevisiae DEAD-box protein Mss116p is a general RNA chaperone that functions in splicing mitochondrial group I and group II introns. Recent X-ray crystal structures of Mss116p in complex with ATP analogs and single-stranded RNA show that the helicase core induces a bend in the bound RNA, as in other DEAD-box proteins, while a C-terminal extension (CTE) induces a second bend, resulting in RNA crimping. Here, we illuminate these structures by using high-throughputgenetic selections, unigenic evolution, and analyses of in vivo splicing activity to comprehensively identify functionally important regions and permissible amino acid substitutions throughout Mss116p. The functionally important regions include those containing conserved sequence motifs involved in ATP and RNA binding or interdomain interactions, as well as previously unidentified regions, including surface loops that may function in protein-protein interactions. The genetic selections recapitulate major features of the conserved helicase motifs seen in other DEAD-box proteins but also show surprising variations, including multiple novel variants of motif III (SAT). Patterns of amino acid substitutions indicate that the RNA bend induced by the helicase core depends on ionic and hydrogen-bonding interactions with the bound RNA; identify a subset of critically interacting residues; and indicate that the bend induced by the CTE results primarily from a steric block. Finally, we identified two conserved regions - one the previously noted post II region in the helicase core and the other in the CTE - that may help displace or sequester the opposite RNA strand during RNA unwinding.

The Saccharomyces cerevisiae DEAD-box protein Mss116p is a general RNA chaperone that functions in splicing mitochondrial group I and group II introns. Recent X-ray crystal structures of Mss116p in complex with ATP analogs and single-stranded RNA show that the helicase core induces a bend in the bound RNA, as in other DEAD-box proteins, while a C-terminal extension induces a second bend, resulting in RNA crimping. Here, we illuminate these structures by using high-throughputgenetic selections, unigenic evolution, and analyses of in vivo splicing activity to comprehensively identify functionally important regions and permissible amino acid substitutions throughout Mss116p. The functionally important regions include those containing conserved sequence motifs involved in ATP and RNA binding or interdomain interactions, as well as previously unidentified regions, including surface loops that may function in protein-protein interactions. The genetic selections recapitulate major features of the conserved helicase motifs seen in other DEAD-box proteins, but also show surprising variations, including multiple novel variants of motif III (SAT). Patterns of amino acid substitutions indicate that the RNA bend induced by the helicase core depends upon ionic and hydrogen-bonding interactions with the bound RNA; identify a subset of critically interacting residues; and indicate that the bend induced by the C-terminal extension results primarily from a steric block. Finally, we identified two conserved regions, one the previously noted post-II region in the helicase core and the other in the C-terminal extension, which may help displace or sequester the opposite RNA strand during RNA unwinding. PMID:21945532

The rapid advancement in high-throughput SNP genotyping technologies along with next generation sequencing (NGS) platforms has decreased the cost, improved the quality of large-scale genome surveys, and allowed specialty crops with limited genomic resources such as carrot (Daucus carota) to access t...

Interest in the genomics of Eucalyptus has skyrocketed thanks to the recent sequencing of the genome of Eucalyptus grandis and to a growing number of large-scale transcriptomic studies. Quantitative reverse transcription-PCR (RT-PCR) is the method of choice for gene expression analysis and can now also be used as a high-throughput method. The selection of appropriate internal controls is becoming of utmost importance to ensure accurate expression results in Eucalyptus. To this end, we selected 21 candidate reference genes and used high-throughput microfluidic dynamic arrays to assess their expression among a large panel of developmental and environmental conditions with a special focus on wood-forming tissues. We analyzed the expression stability of these genes by using three distinct statistical algorithms (geNorm, NormFinder and ΔCt), and used principal component analysis to compare methods and rankings. We showed that the most stable genes identified depended not only on the panel of biological samples considered but also on the statistical method used. We then developed a comprehensive integration of the rankings generated by the three methods and identified the optimal reference genes for 17 distinct experimental sets covering 13 organs and tissues, as well as various developmental and environmental conditions. The expression patterns of Eucalyptus master genes EgMYB1 and EgMYB2 experimentally validated our selection. Our findings provide an important resource for the selection of appropriate reference genes for accurate and reliable normalization of gene expression data in the organs and tissues of Eucalyptus trees grown in a range of conditions including abiotic stresses.

A mix of oligonucleotide probes was used to hybridize soil metagenomic DNA from a fosmid clone library spotted on high density membranes. The pooled radio-labeled probes were designed to target genes encoding glycoside hydrolases GH18, dehalogenases, bacterial laccases and mobile genetic elements (integrases from integrons and insertion sequences). Positive hybridizing spots were affiliated to the corresponding clones in the library and the metagenomic inserts were sequenced. After assembly and annotation, new coding DNA sequences related to genes of interest were identified with low protein similarity against the closest hits in databases. This work highlights the sensitivity of DNA/DNA hybridization techniques as an effective and complementary way to recover novel genes from large metagenomic clone libraries. This study also supports that some of the identified catabolic genes might be associated with horizontal transfer events.

High-throughput phenotyping of root systems requires a combination of specialized techniques and adaptable plant growth, root imaging and software tools. A custom phenotyping platform was designed to capture images of whole root systems, and novel software tools were developed to process and analyse these images. The platform and its components are adaptable to a wide range root phenotyping studies using diverse growth systems (hydroponics, paper pouches, gel and soil) involving several plant species, including, but not limited to, rice, maize, sorghum, tomato and Arabidopsis. The RootReader2D software tool is free and publicly available and was designed with both user-guided and automated features that increase flexibility and enhance efficiency when measuring root growth traits from specific roots or entire root systems during large-scale phenotyping studies. To demonstrate the unique capabilities and high-throughput capacity of this phenotyping platform for studying root systems, genome-wide association studies on rice (Oryza sativa) and maize (Zea mays) root growth were performed and root traits related to aluminium (Al) tolerance were analysed on the parents of the maize nested association mapping (NAM) population.

Usually, the chemical structures of cerebrosides in sea creatures are more complicated than those from terrestrial plants and animals. Very little is known about the method for high-throughput molecular profiling of cerebrosides in sea cucumbers. In this study, cerebrosides from four species of edible sea cucumbers, specifically, Apostichopus japonicas, Thelenota ananas, Acaudina molpadioides and Bohadschia marmorata, were rapidly identified using reversed-phase liquid chromatography-quadrupole-time-of-flight mass spectrometry (RPLC-QToF-MS). [M + H](+) in positive electrospray ionization (ESI) mode were used to obtain the product ion spectra. The cerebroside molecules were selected according to the neutral loss fragments of 180 Da and then identified according to pairs of specific products of long-chain bases (LCB) and their precursor ions. A typical predominant LCB was 2-amino-1,3-dihydroxy-4-heptadecene (d17:1), which was acylated to form saturated and monounsaturated non-hydroxy and monohydroxy fatty acids with 17-25 carbon atoms. Simultaneously, the occurrence of 2-hydroxy-tricosenoic acid (C23:1h) was characteristic of sea cucumber cerebrosides, whereas this molecule was rarely discovered in plants, mammals, or fungi. The profiles of LCB and fatty acids (FA) distribution might be related to the genera of sea cucumber. These data will be useful for identification of cerebrosides using RPLC-QToF-MS.

A real-time reverse transcription-polymerase chain reaction (RT-PCR) assay was developed for the detection of bluetongue virus (BTV) in blood samples. A combination of primers specific for a highly conserved region in RNA segment 5 (based on Mediterranean BTV sequences) and a DNA probe bound to 5'-Taq nuclease-3' minor groove binder (TaqMan MGB) was used to detect a range of isolates. This real-time RT-PCR assay could detect 5.4 x 10(-3) tissue culture infectious doses (TCID50) of virus per milliliter of sample, which was comparable to our current BTV diagnostic nested RT-PCR assay. The assay detected all recent Mediterranean isolates (including serotypes 2, 4, and 16), BTV vaccine strains for serotypes 2 and 4, and 15 out of the 24 BTV reference strains available (all serotypes), but did not detect the related orbiviruses epizootic hemorrhagic disease and African horse sickness viruses. Following assay evaluation, the ability of this assay to identify BTV in recent isolates (2003, 2004) from ovine and bovine samples from an epizootic outbreak in Spain was also tested. Minor nucleotide changes (detected by sequencing viral genomes) within the probe-binding region were found to have a profound effect on virus detection. This assay has the benefits of being fast and simple, and the 96-well format enables large-scale epidemiological screening for BTV, especially when combined with a high-throughput nucleic acid extraction method.

An overview of avian metapneumovirus (aMPV) infection in turkeys and development of a reversegenetics system for aMPV subgroup C (aMPV-C) virus will be presented. By using reversegenetics technology, we generated recombinant aMPV-C viruses containing a different length of glycoprotein (G) gene or...

The lagging annotation of bacterial genomes and the inherent genetic complexity of many phenotypes is hindering the discovery of new drug targets and the development of new antimicrobial agents and vaccines. This unit presents Tn-seq, a method that has made it possible to quantitatively determine fitness for most genes in a microorganism and to screen for quantitative genetic interactions on a genome-wide scale and in a high-throughput fashion. Tn-seq can thus direct studies on the annotation of genes and untangle complex phenotypes. The method is based on the construction of a saturated transposon insertion library. After library selection, changes in the frequency of each insertion mutant are determined by sequencing flanking regions en masse. These changes are used to calculate each mutant's fitness. The method was originally developed for the Gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis, but has now been applied to several different microbial species.

The lagging annotation of bacterial genomes and the inherent genetic complexity of many phenotypes is hindering the discovery of new drug targets and the development of new antimicrobial agents and vaccines. This unit presents Tn-seq, a method that has made it possible to quantitatively determine fitness for most genes in a microorganism and to screen for quantitative genetic interactions on a genome-wide scale and in a high-throughput fashion. Tn-seq can thus direct studies on the annotation of genes and untangle complex phenotypes. The method is based on the construction of a saturated transposon insertion library. After library selection, changes in the frequency of each insertion mutant are determined by sequencing flanking regions en masse. These changes are used to calculate each mutant's fitness. The method was originally developed for the Gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis, but has now been applied to several different microbial species.

Vibrio cholerae, the causative agent of cholera, remains a threat to public health in areas with inadequate sanitation. As a waterborne pathogen, V. cholerae moves between two dissimilar environments, aquatic reservoirs and the intestinal tract of humans. Accordingly, this pathogen undergoes adaptive shifts in gene expression throughout the different stages of its lifecycle. One particular gene, xds, encodes a secreted exonuclease that was previously identified as being induced during infection. Here we sought to identify regulators responsible for the in vivo-specific induction of xds. A transcriptional fusion of xds to two consecutive antibiotic resistance genes was used to select transposon mutants that had inserted within or adjacent to regulatory genes and thereby caused increased expression of the xds fusion under non-inducing conditions. Large pools of selected insertion sites were sequenced in a highthroughput manner using Tn-seq to identify potential mechanisms of xds regulation. Our selection identified the two-component system PhoB/R as the dominant activator of xds expression. In vitro validation confirmed that PhoB, a protein which is only active during phosphate limitation, was responsible for xds activation. Using xds expression as a biosensor of the extracellular phosphate level, we observed that the mouse small intestine is a phosphate-limited environment.

The recent spread of highly pathogenic H5N1 avian influenza (AI) has made it important to develop highly sensitive diagnostic systems for the rapid detection of AI genome and the differentiation of H5N1 variants in a high number of samples. In the present paper, we describe a high-throughput procedure that combines automated extraction, amplification, and detection of AI RNA, by an already described TaqMan real-time reverse transcription-polymerase chain reaction (RRT-PCR) assay targeted at the matrix (M) protein gene of AI virus (AIV). The method was tested in cloacal and tracheal swabs, the most common type of samples used in AI surveillance, as well as in tissue and fecal samples. A robotic system (QIAGEN Biosprint 96) extracted RNA and set up reactions for RRT-PCR in a 96-well format. The recovery of the extracted RNA was as efficient as that of a manual RNA extraction kit, and the sensitivity of the detection system was as high as with previously described nonautomated methods. A system with a basic configuration (one extraction robot plus two real-time 96-well thermocyclers) operated by two persons could account for about 360 samples in 5 hr. Further characterization of AI RNA-positive samples with a TaqMan RRT-PCR specific for H5 (also described here) and/or N1 was possible within 2 hr more. As this work shows, the system can analyze up to 1400 samples per working day by using two nucleic acid extraction robots and a 384-well-format thermocycler.

Mitochondria are central organelles that regulate cellular bioenergetics, biosynthesis, and signaling processes. NADH, a key player in cell metabolism, is often considered as a marker of mitochondrial function. However, traditional methods for NADH measurements are either destructive or unable to distinguish between NADH and NADPH. In contrast to traditional methods, genetically encoded NADH sensors can be used for the real-time tracking and quantitative measurement of subcellular NADH levels in living cells. Therefore, these sensors provide innovative tools and address the limitations of current techniques. We herein summarize the properties of different types of recently developed NADH biosensors, discuss their advantages and disadvantages, and focus on the high-throughput analysis of mitochondrial function by using highly responsive NAD(+)/NADH sensors.

The genetic variants underlying complex traits are often elusive even in powerful model organisms such as Caenorhabditis elegans with controlled genetic backgrounds and environmental conditions. Two major contributing factors are: (1) the lack of statistical power from measuring the phenotypes of small numbers of individuals, and (2) the use of phenotyping platforms that do not scale to hundreds of individuals and are prone to noisy measurements. Here, we generated a new resource of 359 recombinant inbred strains that augments the existing C. elegans N2xCB4856 recombinant inbred advanced intercross line population. This new strain collection removes variation in the neuropeptide receptor gene npr-1, known to have large physiological and behavioral effects on C. elegans and mitigates the hybrid strain incompatibility caused by zeel-1 and peel-1, allowing for identification of quantitative trait loci that otherwise would have been masked by those effects. Additionally, we optimized highly scalable and accurate high-throughput assays of fecundity and body size using the COPAS BIOSORT large particle nematode sorter. Using these assays, we identified quantitative trait loci involved in fecundity and growth under normal growth conditions and after exposure to the herbicide paraquat, including independent genetic loci that regulate different stages of larval growth. Our results offer a powerful platform for the discovery of the genetic variants that control differences in responses to drugs, other aqueous compounds, bacterial foods, and pathogenic stresses. PMID:25770127

The recently developed approach for microsatellite genotyping by sequencing (GBS) using individual combinatorial barcoding was further improved and used to assess the genetic population structure of boarfish (Capros aper) across the species' range. Microsatellite loci were developed de novo and genotyped by next-generation sequencing. Genetic analyses of the samples indicated that boarfish can be subdivided into at least seven biological units (populations) across the species' range. Furthermore, the recent apparent increase in abundance in the northeast Atlantic is better explained by demographic changes within this area than by influx from southern or insular populations. This study clearly shows that the microsatellite GBS approach is a generic, cost-effective, rapid and powerful method suitable for full-scale population genetic studies—a crucial element for assessment, sustainable management and conservation of valuable biological resources. PMID:28083107

Sorghum is an important target for plant genomic mapping because of its adaptation to harsh environments, diverse germplasm collection, and value for comparing the genomes of grass species such as corn and rice. The construction of an integrated genetic and physical map of the sorghum genome (750 Mbp) is a primary goal of our sorghum genome project. To help accomplish this task, we have developed a new high-throughput PCR-based method for building BAC contigs and locating BAC clones on the sorghum genetic map. This task involved pooling 24,576 sorghum BAC clones (∼4× genome equivalents) in six different matrices to create 184 pools of BAC DNA. DNA fragments from each pool were amplified using amplified fragment length polymorphism (AFLP) technology, resolved on a LI-COR dual-dye DNA sequencing system, and analyzed using Bionumerics software. On average, each set of AFLP primers amplified 28 single-copy DNA markers that were useful for identifying overlapping BAC clones. Data from 32 different AFLP primer combinations identified ∼2400 BACs and ordered ∼700 BAC contigs. Analysis of a sorghum RIL mapping population using the same primer pairs located ∼200 of the BAC contigs on the sorghum genetic map. Restriction endonuclease fingerprinting of the entire collection of sorghum BAC clones was applied to test and extend the contigs constructed using this PCR-based methodology. Analysis of the fingerprint data allowed for the identification of 3366 contigs each containing an average of 5 BACs. BACs in ∼65% of the contigs aligned by AFLP analysis had sufficient overlap to be confirmed by DNA fingerprint analysis. In addition, 30% of the overlapping BACs aligned by AFLP analysis provided information for merging contigs and singletons that could not be joined using fingerprint data alone. Thus, the combination of fingerprinting and AFLP-based contig assembly and mapping provides a reliable, high-throughput method for building an integrated genetic and physical map

Metabarcode surveys of DNA extracted from environmental samples are increasingly popular for biodiversity assessment in natural communities. Such surveys rely heavily on robust genetic markers. Therefore, analysis of PCR efficiency and subsequent biodiversity estimation for different types of genetic markers and their corresponding primers is important. Here, we test the PCR efficiency and biodiversity recovery potential of three commonly used genetic markers - nuclear small subunit ribosomal DNA (18S), mitochondrial cytochrome c oxidase subunit I (COI) and 16S ribosomal RNA (mt16S) - using 454 pyrosequencing of a zooplankton community collected from Hamilton Harbour, Ontario. We found that biodiversity detection power and PCR efficiency varied widely among these markers. All tested primers for COI failed to provide high-quality PCR products for pyrosequencing, but newly designed primers for 18S and 16S passed all tests. Furthermore, multiple analyses based on large-scale pyrosequencing (i.e. 1/2 PicoTiter plate for each marker) showed that primers for 18S recover more (38 orders) groups than 16S (10 orders) across all taxa, and four vs. two orders and nine vs. six families for Crustacea. Our results showed that 18S, using newly designed primers, is an efficient and powerful tool for profiling biodiversity in largely unexplored communities, especially when amplification difficulties exist for mitochondrial markers such as COI. Universal primers for higher resolution markers such as COI are still needed to address the possible low resolution of 18S for species-level identification.

This study assessed the genetic diversity in the growth hormone 1 gene (GH1) within and between South African goat breeds. Polymerase chain reaction-targeted gene amplification together with Illumina MiSeq next-generation sequencing (NGS) was used to generate the full length (2.54 kb) of the growth hormone 1 gene and screen for SNPs in the South African Boer (SAB) (n = 17), Tankwa (n = 15) and South African village (n = 35) goat populations. A range of 27-58 SNPs per population were observed. Mutations resulting in amino acid changes were observed at exons 2 and 5. Higher within-breed diversity of 97.37% was observed within the population category consisting of SA village ecotypes and the Tankwa goats. Highest pairwise FST values ranging from 0.148 to 0.356 were observed between the SAB and both the South African village and Tankwa feral goat populations. Phylogenetic analysis indicated nine genetic clusters, which reflected close relationships between the South African populations and the other international breeds with the exception of the Italian Sarda breeds. Results imply greater potential for within-population selection programs, particularly with SA village goats.

The lagging annotation of bacterial genomes and the inherent genetic complexity of many phenotypes is hindering the discovery of new drug targets and the development of new antimicrobials and vaccines. Here we present the method Tn-seq, with which it has become possible to quantitatively determine fitness for most genes in a microorganism and to screen for quantitative genetic interactions on a genome-wide scale and in a high-throughput fashion. Tn-seq can thus direct studies in the annotation of genes and untangle complex phenotypes. The method is based on the construction of a saturated Mariner transposon insertion library. After library selection, changes in frequency of each insertion mutant are determined by sequencing of the flanking regions en masse. These changes are used to calculate each mutant's fitness. The method has been developed for the Gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis; however, due to the wide activity of the Mariner transposon, Tn-seq can be applied to many different microbial species.

To date, no large scale, systematic description of the blood serum proteome has been performed in inflammatory bowel disease (IBD) patients. By using microarray technology, a more complete description of the blood proteome of IBD patients is feasible. It may help to achieve a better understanding of the disease. We analyzed blood serum profiles of 1128 proteins in IBD patients of European descent (84 Crohn’s Disease (CD) subjects and 88 Ulcerative Colitis (UC) subjects) as well as 15 healthy control subjects, and linked protein variability to patient age (all cohorts) and genetic components (genotype data generated from CD patients). We discovered new, previously unreported aging-associated proteomic traits (such as serum Albumin level), confirmed previously reported results from different tissues (i.e., upregulation of APOE with aging), and found loss of regulation of MMP7 in CD patients. In carrying out a genome wide genotype-protein association study (proteomic Quantitative Trait Loci, pQTL) within the CD patients, we identified 41 distinct proteomic traits influenced by cis pQTLs (underlying SNPs are referred to as pSNPs). Significant overlaps between pQTLs and cis eQTLs corresponding to the same gene were observed and in some cases the QTL were related to inflammatory disease susceptibility. Importantly, we discovered that serum protein levels of MST1 (Macrophage Stimulating 1) were regulated by SNP rs3197999 (p = 5.96E-10, FDR<5%), an accepted GWAS locus for IBD. Filling the knowledge gap of molecular mechanisms between GWAS hits and disease susceptibility requires systematically dissecting the impact of the locus at the cell, mRNA expression, and protein levels. The technology and analysis tools that are now available for large-scale molecular studies can elucidate how alterations in the proteome driven by genetic polymorphisms cause or provide protection against disease. Herein, we demonstrated this directly by integrating proteomic and pQTLs with

To date, no large scale, systematic description of the blood serum proteome has been performed in inflammatory bowel disease (IBD) patients. By using microarray technology, a more complete description of the blood proteome of IBD patients is feasible. It may help to achieve a better understanding of the disease. We analyzed blood serum profiles of 1128 proteins in IBD patients of European descent (84 Crohn's Disease (CD) subjects and 88 Ulcerative Colitis (UC) subjects) as well as 15 healthy control subjects, and linked protein variability to patient age (all cohorts) and genetic components (genotype data generated from CD patients). We discovered new, previously unreported aging-associated proteomic traits (such as serum Albumin level), confirmed previously reported results from different tissues (i.e., upregulation of APOE with aging), and found loss of regulation of MMP7 in CD patients. In carrying out a genome wide genotype-protein association study (proteomic Quantitative Trait Loci, pQTL) within the CD patients, we identified 41 distinct proteomic traits influenced by cis pQTLs (underlying SNPs are referred to as pSNPs). Significant overlaps between pQTLs and cis eQTLs corresponding to the same gene were observed and in some cases the QTL were related to inflammatory disease susceptibility. Importantly, we discovered that serum protein levels of MST1 (Macrophage Stimulating 1) were regulated by SNP rs3197999 (p = 5.96E-10, FDR<5%), an accepted GWAS locus for IBD. Filling the knowledge gap of molecular mechanisms between GWAS hits and disease susceptibility requires systematically dissecting the impact of the locus at the cell, mRNA expression, and protein levels. The technology and analysis tools that are now available for large-scale molecular studies can elucidate how alterations in the proteome driven by genetic polymorphisms cause or provide protection against disease. Herein, we demonstrated this directly by integrating proteomic and pQTLs with existing

The analysis and profiling of short tandem repeat (STR) loci is routinely used in forensic genetics. Current methods to investigate STR loci, including PCR-based standard fragment analyses and capillary electrophoresis, only provide amplicon lengths that are used to estimate the number of STR repeat units. These methods do not allow for the full resolution of STR base composition that sequencing approaches could provide. Here we present an STR profiling method based on the use of the Roche Genome Sequencer (GS) FLX to simultaneously sequence multiple core STR loci. Using this method in combination with a bioinformatic tool designed specifically to analyze sequence lengths and frequencies, we found that GS FLX STR sequence data are comparable to conventional capillary electrophoresis-based STR typing. Furthermore, we found DNA base substitutions and repeat sequence variations that would not have been identified using conventional STR typing.

The highly pathogenic Marburg virus (MARV) is a member of the Filoviridae family and belongs to the group of nonsegmented negative-strand RNA viruses. Reversegenetics systems established for MARV have been used to study various aspects of the viral replication cycle, analyze host responses, image viral infection, and screen for antivirals. This article provides an overview of the currently established MARV reversegenetic systems based on minigenomes, infectious virus-like particles and full-length clones, and the research that has been conducted using these systems. PMID:27338448

The highly pathogenic Marburg virus (MARV) is a member of the Filoviridae family and belongs to the group of nonsegmented negative-strand RNA viruses. Reversegenetics systems established for MARV have been used to study various aspects of the viral replication cycle, analyze host responses, image viral infection, and screen for antivirals. This article provides an overview of the currently established MARV reversegenetic systems based on minigenomes, infectious virus-like particles and full-length clones, and the research that has been conducted using these systems.

Slotted WDM, which achieves higher capacity compared with conventional WDM and SDH networks, has been discussed a lot recently. The ring network for this architecture has been demonstrated experimentally. In slotted WDM ring network, each node is equipped with a wavelength-tunable transmitter and a fixed receiver and assigned with a specific wavelength. A node can send data to every other node by tuning wavelength accordingly in a time slot. One of the important issues for it is scheduling. Scheduling of it can be reduced to input queued switch when synchronization and propagation are solved and many schemes have been proposed to solve these two issues. However, it"s proved that scheduling of such a network taking both jitter and throughput into consideration is NP hard. Greedy algorithm has been proposed to solve it before. The main contribution of this paper lies in a novel genetic algorithm to obtain optimal or near optimal value of this specific NP hard problem. We devise problem specific chromosome codes, fitness function, crossover and mutation operations. Experimental results show that our GA provides better performances in terms of throughput and jitter than a greedy heuristic.

Proteomics has become a major focus as researchers attempt to understand the vast amount of genomic information. Protein complexity makes identifying and understanding gene function inherently difficult. The challenge of studying proteins in a global way is driving the development of new technologies for systematic and comprehensive analysis of protein structure and function. We are addressing this challenge through instrumentation and approaches to rapidly express, purify, crystallize, and mutate large numbers of human gene products. Our approach applies the principles of HTS technologies commonly used in pharmaceutical development. Genes are cloned, expressed, and purified in parallel to achieve a throughput potential of hundreds per day. Our instrumentation allows us to produce tens of milligrams of protein from 96 separate clones simultaneously. Purified protein is used for several applications including a high-throughput crystallographic screening approach for structure determination using automated image analysis. To further understand protein function, we are integrating a mutagenesis and screening approach. By combining these key technologies, we hope to provide a fundamental basis for understanding gene function at the protein level.

A scanning apparatus is provided to obtain automated, rapid and sensitive scanning of substrate fluorescence, optical density or phosphorescence. The scanner uses a constant path length optical train, which enables the combination of a moving beam for high speed scanning with phase-sensitive detection for noise reduction, comprising a light source, a scanning mirror to receive light from the light source and sweep it across a steering mirror, a steering mirror to receive light from the scanning mirror and reflect it to the substrate, whereby it is swept across the substrate along a scan arc, and a photodetector to receive emitted or scattered light from the substrate, wherein the optical path length from the light source to the photodetector is substantially constant throughout the sweep across the substrate. The optical train can further include a waveguide or mirror to collect emitted or scattered light from the substrate and direct it to the photodetector. For phase-sensitive detection the light source is intensity modulated and the detector is connected to phase-sensitive detection electronics. A scanner using a substrate translator is also provided. For two dimensional imaging the substrate is translated in one dimension while the scanning mirror scans the beam in a second dimension. For a highthroughput scanner, stacks of substrates are loaded onto a conveyor belt from a tray feeder.

The rotavirus genome is composed of 11 gene segments of dsRNA. A recent breakthrough in the field of rotaviruses is the development of a reversegenetics system for generating recombinant rotaviruses possessing a gene segment derived from cloned cDNA. Although this approach is a helper virus-driven system that is technically limited and gives low levels of recombinant viruses, it allows alteration of the rotavirus genome, thus contributing to our understanding of these medically important viruses. So far, this approach has successfully been applied to three of the 11 viral segments in our laboratory and others, and the efficiency of recovery of recombinant viruses has been improved. However, we are still waiting for the development of a helper virus-free reversegenetics system for generating an infectious rotavirus entirely from cDNAs, as has been achieved for other members of the Reoviridae family.

We have here applied high-throughput amplified fragment length polymorphism (htAFLP) analysis to strains belonging to the five classical species of the Mycobacterium tuberculosis complex. Using 20 strains, three enzyme combinations and eight selective amplification primer pairs, 24 AFLP reactions were performed per strain. Overall, this resulted in 480 DNA fingerprints and more than 1200 htAFLP-amplified PCR fragments were visualised per strain. The cumulative dendrogram correctly clustered strains from the various species, albeit within a distance of 6.5% for most of them. The single isolate of Mycobacterium canettii presented separately at 19% distance. All over, 169 fragments (14%) appeared to be polymorphic. Sixty-eight were specific for M. canetti and forty-five for Mycobacterium bovis. For the 10 different M. tuberculosis strains included in the present analysis, 56 polymorphic markers were identified. Upon sequencing 20 of these marker regions and comparisons with the H37Rv genome sequence, 25% appeared to share homology to members of the antigenically variable PE/PPE surface protein encoding gene family confirming previous findings on the genetic heterogeneity within these genes. In addition, homologues for phage genes and insertion element-encoded genes were detected. Forty-five percent of the sequences derived from ORFs with a currently unknown function, which was corroborated by genome sequence comparison for the clinical M. tuberculosis CD 1551 isolate. Sequence variation in M. tuberculosis was assessed in more detail for a subset of these loci by newly designed PCR restriction fragment length polymorphism (RFLP) tests and direct sequencing. Fourteen novel PCR RFLP tests were developed and twelve novel single nucleotide polymorphisms (SNPs) were identified, all suited for epidemiological analysis of M. tuberculosis. The tests allowed for identification of the major Mycobacterium species and M. tuberculosis variants and clones.

A new approach has been developed by modifying a conventional gradient elution liquid chromatograph for the highthroughput screening of biological samples to detect the presence of regulated intoxicants. The goal of this work was to improve the speed of a gradient elution screening method over current approaches by optimizing the operational parameters of both the column and the instrument without compromising the reproducibility of the retention times, which are the basis for the identification. Most importantly, the novel instrument configuration substantially reduces the time needed to re-equilibrate the column between gradient runs, thereby reducing the total time for each analysis. The total analysis time for each gradient elution run is only 2.8 minutes, including 0.3 minutes for column reequilibration between analyses. Retention times standard calibration solutes are reproducible to better than 0.002 minutes in consecutive runs. A corrected retention index was adopted to account for day-to-day and column-to-column variations in retention time. The discriminating power and mean list length were calculated for a library of 47 intoxicants and compared with previous work from other laboratories to evaluate fast gradient elution HPLC as a screening tool.

We demonstrate a high-throughput platform for cellular-resolution in vivo pharmaceutical and genetic screens on zebrafish larvae. The system automatically loads animals from reservoirs or multiwell plates, and positions and orients them for high-speed confocal imaging and laser manipulation of both superficial and deep organs within 19 seconds without damage. We show small-scale test screening of retinal axon guidance mutants and neuronal regeneration assays in combination with femtosecond laser microsurgery. PMID:20639868

By precisely manipulating the expression of individual genetic elements thought to be important for ecological performance, reversegenetics has the potential to revolutionize plant ecology. However, untested concerns about possible side-effects of the transformation technique, caused by Agrobacterium infection and tissue culture, on plant performance have stymied research by requiring onerous sample sizes. We compare 5 independently transformed Nicotiana attenuata lines harboring empty vector control (EVC) T-DNA lacking silencing information with isogenic wild types (WT), and measured a battery of ecologically relevant traits, known to be important in plant-herbivore interactions: phytohormones, secondary metabolites, growth and fitness parameters under stringent competitive conditions, and transcriptional regulation with microarrays. As a positive control, we included a line silenced in trypsin proteinase inhibitor gene (TPI) expression, a potent anti-herbivore defense known to exact fitness costs in its expression, in the analysis. The experiment was conducted twice, with 10 and 20 biological replicates per genotype. For all parameters, we detected no difference between any EVC and WT lines, but could readily detect a fitness benefit of silencing TPI production. A statistical power analyses revealed that the minimum sample sizes required for detecting significant fitness differences between EVC and WT was 2–3 orders of magnitude larger than the 10 replicates required to detect a fitness effect of TPI silencing. We conclude that possible side-effects of transformation are far too low to obfuscate the study of ecologically relevant phenotypes. PMID:18253491

This study makes a significant advancement on a microRNA amplification technique previously used for expression analysis and sequencing in animal models without annotated mature microRNA sequences. As research progresses into the post-genomic era of microRNA prediction and analysis, the need for a rapid and cost-effective method for microRNA amplification is critical to facilitate wide-scale analysis of microRNA expression. To facilitate this requirement, we have reoptimized the design of amplification primers and introduced a polyadenylation step to allow amplification of all mature microRNAs from a single RNA sample. Importantly, this method retains the ability to sequence reverse transcription polymerase chain reaction (RT-PCR) products, validating microRNA-specific amplification.

Brassica napus (rapeseed) is a recent allotetraploid plant and the second most important oilseed crop worldwide. The origin of B. napus and the genetic relationships with its diploid ancestor species remain largely unresolved. Here, chloroplast DNA (cpDNA) from 488 B. napus accessions of global origin, 139 B. rapa accessions and 49 B. oleracea accessions were populationally resequenced using Illumina Solexa sequencing technologies. The intraspecific cpDNA variants and their allelic frequencies were called genomewide and further validated via EcoTILLING analyses of the rpo region. The cpDNA of the current global B. napus population comprises more than 400 variants (SNPs and short InDels) and maintains one predominant haplotype (Bncp1). Whole-genome resequencing of the cpDNA of Bncp1 haplotype eliminated its direct inheritance from any accession of the B. rapa or B. oleracea species. The distribution of the polymorphism information content (PIC) values for each variant demonstrated that B. napus has much lower cpDNA diversity than B. rapa; however, a vast majority of the wild and cultivated B. oleracea specimens appeared to share one same distinct cpDNA haplotype, in contrast to its wild C-genome relatives. This finding suggests that the cpDNA of the three Brassica species is well differentiated. The predominant B. napus cpDNA haplotype may have originated from uninvestigated relatives or from interactions between cpDNA mutations and natural/artificial selection during speciation and evolution. These exhaustive data on variation in cpDNA would provide fundamental data for research on cpDNA and chloroplasts.

Lysine specific demethylase 1 KDM1A (LSD1) regulates histone methylation and it is increasingly recognized as a potential therapeutic target in oncology. We report on a high-throughput screening campaign performed on KDM1A/CoREST, using a time-resolved fluorescence resonance energy transfer (TR-FRET) technology, to identify reversible inhibitors. The screening led to 115 hits for which we determined biochemical IC50, thus identifying four chemical series. After data analysis, we have prioritized the chemical series of N-phenyl-4H-thieno[3, 2-b]pyrrole-5-carboxamide for which we obtained X-ray structures of the most potent hit (compound 19, IC50 = 2.9 μM) in complex with the enzyme. Initial expansion of this chemical class, both modifying core structure and decorating benzamide moiety, was directed toward the definition of the moieties responsible for the interaction with the enzyme. Preliminary optimization led to compound 90, which inhibited the enzyme with a submicromolar IC50 (0.162 μM), capable of inhibiting the target in cells.

RNA viruses are capable of rapid spread and severe or potentially lethal disease in both animals and humans. The development of reversegenetics systems for manipulation and study of RNA virus genomes has provided platforms for designing and optimizing viral mutants for vaccine development. Here, we review the impact of RNA virus reversegenetics systems on past and current efforts to design effective and safe viral therapeutics and vaccines.

Methods, compositions, and kits for the cell-free production and analysis of proteins are provided. The invention allows for the production of proteins from prokaryotic sequences or eukaryotic sequences, including human cDNAs using PCR and IVT methods and detecting the proteins through fluorescence or immunoblot techniques. This invention can be used to identify optimized PCR and WT conditions, codon usages and mutations. The methods are readily automated and can be used for highthroughput analysis of protein expression levels, interactions, and functional states.

Summary The human genome sequence has profoundly altered our understanding of biology, human diversity and disease. The path from the first draft sequence to our nascent era of personal genomes and genomic medicine has been made possible only because of the extraordinary advancements in DNA sequencing technologies over the past ten years. Here, we discuss commonly used high-throughput sequencing platforms, the growing array of sequencing assays developed around them as well as the challenges facing current sequencing platforms and their clinical application. PMID:26000844

In high-throughput experiments, the sample size is typically chosen informally. Most formal sample-size calculations depend critically on prior knowledge. We propose a sequential strategy that, by updating knowledge when new data are available, depends less critically on prior assumptions. Experiments are stopped or continued based on the potential benefits in obtaining additional data. The underlying decision-theoretic framework guarantees the design to proceed in a coherent fashion. We propose intuitively appealing, easy-to-implement utility functions. As in most sequential design problems, an exact solution is prohibitive. We propose a simulation-based approximation that uses decision boundaries. We apply the method to RNA-seq, microarray, and reverse-phase protein array studies and show its potential advantages. The approach has been added to the Bioconductor package gaga.

Background Influenza viruses display a high mutation rate and complex evolutionary patterns. Next-generation sequencing (NGS) has been widely used for qualitative and semi-quantitative assessment of genetic diversity in complex biological samples. The “deep sequencing” approach, enabled by the enormous throughput of current NGS platforms, allows the identification of rare genetic viral variants in targeted genetic regions, but is usually limited to a small number of samples. Methodology and Principal Findings We designed a proof-of-principle study to test whether redistributing sequencing throughput from a high depth-small sample number towards a low depth-large sample number approach is feasible and contributes to influenza epidemiological surveillance. Using 454-Roche sequencing, we sequenced at a rather low depth, a 307 bp amplicon of the neuraminidase gene of the Influenza A(H1N1) pandemic (A(H1N1)pdm) virus from cDNA amplicons pooled in 48 barcoded libraries obtained from nasal swab samples of infected patients (n = 299) taken from May to November, 2009 pandemic period in Mexico. This approach revealed that during the transition from the first (May-July) to second wave (September-November) of the pandemic, the initial genetic variants were replaced by the N248D mutation in the NA gene, and enabled the establishment of temporal and geographic associations with genetic diversity and the identification of mutations associated with oseltamivir resistance. Conclusions NGS sequencing of a short amplicon from the NA gene at low sequencing depth allowed genetic screening of a large number of samples, providing insights to viral genetic diversity dynamics and the identification of genetic variants associated with oseltamivir resistance. Further research is needed to explain the observed replacement of the genetic variants seen during the second wave. As sequencing throughput rises and library multiplexing and automation improves, we foresee that the approach

Clostridium sporogenes PA 3679 is a nonpathogenic, nontoxic model organism for proteolytic Clostridium botulinum used in the validation of conventional thermal food processes due to its ability to produce highly heat-resistant endospores. Because of its public safety importance, the uncertain taxonomic classification and genetic diversity of PA 3679 are concerns. Therefore, isolates of C. sporogenes PA 3679 were obtained from various sources and characterized using pulsed-field gel electrophoresis (PFGE) and whole-genome sequencing. The phylogenetic relatedness and genetic variability were assessed based on 16S rRNA gene sequencing and whole-genome single nucleotide polymorphism (SNP) analysis. All C. sporogenes PA 3679 isolates were categorized into two clades (clade I containing ATCC 7955 NCA3679 isolates 1961-2, 1990, and 2007 and clade II containing PA 3679 isolates NFL, UW, FDA, and Campbell and ATCC 7955 NCA3679 isolate 1961-4). The 16S maximum likelihood (ML) tree clustered both clades within proteolytic C. botulinum strains, with clade I forming a distinct cluster with other C. sporogenes non-PA 3679 strains. SNP analysis revealed that clade I isolates were more similar to the genomic reference PA 3679 (NCTC8594) genome (GenBank accession number AGAH00000000.1) than clade II isolates were. The genomic reference C. sporogenes PA 3679 (NCTC8594) genome and clade I C. sporogenes isolates were genetically distinct from those obtained from other sources (University of Wisconsin, National Food Laboratory, U.S. Food and Drug Administration, and Campbell's Soup Company). Thermal destruction studies revealed that clade I isolates were more sensitive to high temperature than clade II isolates were. Considering the widespread use of C. sporogenes PA 3679 and its genetic information in numerous studies, the accurate identification and genetic characterization of C. sporogenes PA 3679 are of critical importance. PMID:26519392

This article reviews the origin and evolution of highthroughput screening (HTS) through the experience of an individual pharmaceutical company, revealing some of the mysteries of the early stages of drug discovery to the wider pharmacology audience. HTS in this company (Pfizer, Groton, USA) had its origin in natural products screening in 1986, by substituting fermentation broths with dimethyl sulphoxide solutions of synthetic compounds, using 96-well plates and reduced assay volumes of 50-100μl. A nominal 30mM source compound concentration provided high μM assay concentrations. Starting at 800 compounds each week, the process reached a steady state of 7200 compounds per week by 1989. Screening in the Applied Biotechnology and Screening Group was centralized with screens operating in lock-step to maximize efficiency. Initial screens were full files run in triplicate. Autoradiography and image analysis were introduced for 125I receptor ligand screens. Reverse transcriptase (RT) coupled with quantitative PCR and multiplexing addressed several targets in a single assay. By 1992 HTS produced ‘hits' as starting matter for approximately 40% of the Discovery portfolio. In 1995, the HTS methodology was expanded to include ADMET targets. ADME targets required each compound to be physically detected leading to the development of automated highthroughput LC-MS. In 1996, 90 compounds/week were screened in microsomal, protein binding and serum stability assays. Subsequently, the mutagenic Ames assay was adapted to a 96-well plate liquid assay and novel algorithms permitted automated image analysis of the micronucleus assay. By 1999 ADME HTS was fully integrated into the discovery cycle. PMID:17603542

The troublesome emergence of new classes of micro-pollutants, such as pharmaceuticals and endocrine disruptors, poses challenges for conventional water treatment systems. In an effort to address these contaminants and to support water reuse in drought stricken regions, new technologies must be introduced. The interaction of water with plasma rapidly mineralizes organics by inducing advanced oxidation in addition to other chemical, physical and radiative processes. The primary barrier to the implementation of plasma-based water treatment is process volume scale up. In this work, we investigate a potentially scalable, highthroughput plasma water reactor that utilizes a packed bed dielectric barrier-like geometry to maximize the plasma-water interface. Here, the water serves as the dielectric medium. High-speed imaging and emission spectroscopy are used to characterize the reactor discharges. Changes in methylene blue concentration and basic water parameters are mapped as a function of plasma treatment time. Experimental results are compared to electrostatic and plasma chemistry computations, which will provide insight into the reactor's operation so that efficiency can be assessed. Supported by NSF (CBET 1336375).

Voltage-clamp techniques are typically used to study the plasma membrane proteins, such as ion channels and transporters that control bioelectrical signals. Many of these proteins have been cloned and can now be studied as potential targets for drug development. The two approaches most commonly used for heterologous expression of cloned ion channels and transporters involve either transfection of the genes into small cells grown in tissue culture or the injection of the genetic material into larger cells. The standard large cells used for the expression of cloned cDNA or synthetic RNA are the egg progenitor cells (oocytes) of the African frog, Xenopus laevis. Until recently, cellular electrophysiology was performed manually, one cell at a time by a single operator. However, methods of high-throughput electrophysiology have been developed which are automated and permit data acquisition and analysis from multiple cells in parallel. These methods are breaking a bottleneck in drug discovery, useful in some cases for primary screening as well as for thorough characterization of new drugs. Increasing throughput of high-quality functional data greatly augments the efficiency of academic research and pharmaceutical drug development. Some examples of studies that benefit most from high-throughput electrophysiology include pharmaceutical screening of targeted compound libraries, secondary screening of identified compounds for subtype selectivity, screening mutants of ligand-gated channels for changes in receptor function, scanning mutagenesis of protein segments, and mutant-cycle analysis. We describe here the main features and potential applications of OpusXpress, an efficient commercially available system for automated recording from Xenopus oocytes. We show some types of data that have been gathered by this system and review realized and potential applications. PMID:19149490

The C-terminal domain (CTD) of RNA polymerase II (RNAPII) is composed of heptapeptide repeats, which play a key regulatory role in gene expression. Using genetic interaction, chromatin immunoprecipitation followed by microarrays (ChIP-on-chip) and mRNA expression analysis, we found that truncating the CTD resulted in distinct changes to cellular function. Truncating the CTD altered RNAPII occupancy, leading to not only decreases, but also increases in mRNA levels. The latter were largely mediated by promoter elements and in part were linked to the transcription factor Rpn4. The mediator subunit Cdk8 was enriched at promoters of these genes, and its removal not only restored normal mRNA and RNAPII occupancy levels, but also reduced the abnormally high cellular amounts of Rpn4. This suggested a positive role of Cdk8 in relationship to RNAPII, which contrasted with the observed negative role at the activated INO1 gene. Here, loss of CDK8 suppressed the reduced mRNA expression and RNAPII occupancy levels of CTD truncation mutants. PMID:24009531

Characterizing the genetic diversity of microbial copper (Cu) resistance at the community level remains challenging, mainly due to the polymorphism of the core functional gene copA. In this study, a local BLASTN method using a copA database built in this study was developed to recover full-length putative copA sequences from an assembled tailings metagenome; these sequences were then screened for potentially functioning CopA using conserved metal-binding motifs, inferred by evolutionary trace analysis of CopA sequences from known Cu resistant microorganisms. In total, 99 putative copA sequences were recovered from the tailings metagenome, out of which 70 were found with high potential to be functioning in Cu resistance. Phylogenetic analysis of selected copA sequences detected in the tailings metagenome showed that topology of the copA phylogeny is largely congruent with that of the 16S-based phylogeny of the tailings microbial community obtained in our previous study, indicating that the development of copA diversity in the tailings might be mainly through vertical descent with few lateral gene transfer events. The method established here can be used to explore copA (and potentially other metal resistance genes) diversity in any metagenome and has the potential to exhaust the full-length gene sequences for downstream analyses. PMID:26286020

High-throughput SNP genotyping provides a rapid way of developing resourceful set of markers for delineating the genetic architecture and for effective species discrimination. In the presented research, we demonstrate a set of 192 SNPs for effective genotyping in sugar beet using high-throughput mar...

Several arenavirus cause hemorrhagic fever disease in humans and pose a significant public health problem in their endemic regions. To date, no licensed vaccines are available to combat human arenavirus infections, and anti-arenaviral drug therapy is limited to an off-label use of ribavirin that is only partially effective. The development of arenavirus reversegenetics approaches provides investigators with a novel and powerful approach for the investigation of the arenavirus molecular and cell biology. The use of cell-based minigenome systems has allowed examining the cis- and trans-acting factors involved in arenavirus replication and transcription and the identification of novel anti-arenaviral drug targets without requiring the use of live forms of arenaviruses. Likewise, it is now feasible to rescue infectious arenaviruses entirely from cloned cDNAs containing predetermined mutations in their genomes to investigate virus-host interactions and mechanisms of pathogenesis, as well as to facilitate screens to identify anti-arenaviral drugs and development of novel live-attenuated arenavirus vaccines. Recently, reversegenetics have also allowed the generation of tri-segmented arenaviruses expressing foreign genes, facilitating virus detection and opening the possibility of implementing live-attenuated arenavirus-based vaccine vector approaches. Likewise, the development of single-cycle infectious, reporter-expressing, arenaviruses has provided a new experimental method to study some aspects of the biology of highly pathogenic arenaviruses without the requirement of high-security biocontainment required to study HF-causing arenaviruses. In this chapter we summarize the current knowledge on arenavirus reversegenetics and the implementation of plasmid-based reversegenetics techniques for the development of arenavirus vaccines and vaccine vectors. PMID:27076139

Several arenavirus cause hemorrhagic fever disease in humans and pose a significant public health problem in their endemic regions. To date, no licensed vaccines are available to combat human arenavirus infections, and anti-arenaviral drug therapy is limited to an off-label use of ribavirin that is only partially effective. The development of arenavirus reversegenetics approaches provides investigators with a novel and powerful approach for the investigation of the arenavirus molecular and cell biology. The use of cell-based minigenome systems has allowed examining the cis- and trans-acting factors involved in arenavirus replication and transcription and the identification of novel anti-arenaviral drug targets without requiring the use of live forms of arenaviruses. Likewise, it is now feasible to rescue infectious arenaviruses entirely from cloned cDNAs containing predetermined mutations in their genomes to investigate virus-host interactions and mechanisms of pathogenesis, as well as to facilitate screens to identify anti-arenaviral drugs and development of novel live-attenuated arenavirus vaccines. Recently, reversegenetics have also allowed the generation of tri-segmented arenaviruses expressing foreign genes, facilitating virus detection and opening the possibility of implementing live-attenuated arenavirus-based vaccine vector approaches. Likewise, the development of single-cycle infectious, reporter-expressing, arenaviruses has provided a new experimental method to study some aspects of the biology of highly pathogenic arenaviruses without the requirement of high-security biocontainment required to study HF-causing arenaviruses. In this chapter we summarize the current knowledge on arenavirus reversegenetics and the implementation of plasmid-based reversegenetics techniques for the development of arenavirus vaccines and vaccine vectors.

ABSTRACT The notoriously low efficiency of Paramyxoviridae reversegenetics systems has posed a limiting barrier to the study of viruses in this family. Previous approaches to reversegenetics have utilized a wide variety of techniques to overcome the technical hurdles. Although robustness (i.e., the number of attempts that result in successful rescue) has been improved in some systems with the use of stable cell lines, the efficiency of rescue (i.e., the proportion of transfected cells that yield at least one successful rescue event) has remained low. We have substantially increased rescue efficiency for representative viruses from all five major Paramyxoviridae genera (from ~1 in 106-107 to ~1 in 102-103 transfected cells) by the addition of a self-cleaving hammerhead ribozyme (Hh-Rbz) sequence immediately preceding the start of the recombinant viral antigenome and the use of a codon-optimized T7 polymerase (T7opt) gene to drive paramyxovirus rescue. Here, we report a strategy for robust, reliable, and high-efficiency rescue of paramyxovirus reversegenetics systems, featuring several major improvements: (i) a vaccinia virus-free method, (ii) freedom to use any transfectable cell type for viral rescue, (iii) a single-step transfection protocol, and (iv) use of the optimal T7 promoter sequence for high transcription levels from the antigenomic plasmid without incorporation of nontemplated G residues. The robustness of our T7opt-HhRbz system also allows for greater latitude in the ratios of transfected accessory plasmids used that result in successful rescue. Thus, our system may facilitate the rescue and interrogation of the increasing number of emerging paramyxoviruses. IMPORTANCE The ability to manipulate the genome of paramyxoviruses and evaluate the effects of these changes at the phenotypic level is a powerful tool for the investigation of specific aspects of the viral life cycle and viral pathogenesis. However, reversegenetics systems for paramyxoviruses

The objective of this study was to investigate if feeding genetically modified (GM) MON810 maize expressing the Bacillus thuringiensis insecticidal protein (Bt maize) had any effects on the porcine intestinal microbiota. Eighteen pigs were weaned at ~28 days and, following a 6-day acclimatization period, were assigned to diets containing either GM (Bt MON810) maize or non-GM isogenic parent line maize for 31 days (n = 9/treatment). Effects on the porcine intestinal microbiota were assessed through culture-dependent and -independent approaches. Fecal, cecal, and ileal counts of total anaerobes, Enterobacteriaceae, and Lactobacillus were not significantly different between pigs fed the isogenic or Bt maize-based diets. Furthermore, high-throughput 16S rRNA gene sequencing revealed few differences in the compositions of the cecal microbiotas. The only differences were that pigs fed the Bt maize diet had higher cecal abundance of Enterococcaceae (0.06 versus 0%; P < 0.05), Erysipelotrichaceae (1.28 versus 1.17%; P < 0.05), and Bifidobacterium (0.04 versus 0%; P < 0.05) and lower abundance of Blautia (0.23 versus 0.40%; P < 0.05) than pigs fed the isogenic maize diet. A lower enzyme-resistant starch content in the Bt maize, which is most likely a result of normal variation and not due to the genetic modification, may account for some of the differences observed within the cecal microbiotas. These results indicate that Bt maize is well tolerated by the porcine intestinal microbiota and provide additional data for safety assessment of Bt maize. Furthermore, these data can potentially be extrapolated to humans, considering the suitability of pigs as a human model.

Reversegenetic techniques harnessing mutational approaches are powerful tools that can provide substantial insight into gene function in plants. However, as compared to diploid species, reversegenetic analyses in polyploid plants such as bread wheat can present substantial challenges associated with high levels of sequence and functional similarity amongst homoeologous loci. We previously developed a high-throughput method to identify deletions of genes within a physically mutagenized wheat population. Here we describe our efforts to combine multiple homoeologous deletions of three candidate disease susceptibility genes (TaWRKY11, TaPFT1 and TaPLDß1). We were able to produce lines featuring homozygous deletions at two of the three homoeoloci for all genes, but this was dependent on the individual mutants used in crossing. Intriguingly, despite extensive efforts, viable lines possessing homozygous deletions at all three homoeoloci could not be produced for any of the candidate genes. To investigate deletion size as a possible reason for this phenomenon, we developed an amplicon sequencing approach based on synteny to Brachypodium distachyon to assess the size of the deletions removing one candidate gene (TaPFT1) in our mutants. These analyses revealed that genomic deletions removing the locus are relatively large, resulting in the loss of multiple additional genes. The implications of this work for the use of heavy ion mutagenesis for reversegenetic analyses in wheat are discussed. PMID:25719507

The nematode Caenorhabditis elegans is widely used as a model organism in the field of neurobiology. The wiring of the C. elegans nervous system has been entirely mapped, and the animal's optical transparency allows for in vivo observation of neuronal activity. The nematode is also small in size, self-fertilizing, and inexpensive to cultivate and maintain, greatly lending to its utility as a whole-animal model for high-throughput screening (HTS) in the nervous system. However, the use of this organism in large-scale screens presents unique technical challenges, including reversible immobilization of the animal, parallel single-animal culture and containment, automation of laser surgery, and high-throughput image acquisition and phenotyping. These obstacles require significant modification of existing techniques and the creation of new C. elegans-based HTS platforms. In this review, we outline these challenges in detail and survey the novel technologies and methods that have been developed to address them.

Arenaviruses are important human pathogens with no Food and Drug Administration (FDA)-licensed vaccines available and current antiviral therapy being limited to an off-label use of the nucleoside analogue ribavirin of limited prophylactic efficacy. The development of reversegenetics systems represented a major breakthrough in arenavirus research. However, rescue of recombinant arenaviruses using current reversegenetics systems has been restricted to rodent cells. In this study, we describe the rescue of recombinant arenaviruses from human 293T cells and Vero cells, an FDA-approved line for vaccine development. We also describe the generation of novel vectors that mediate synthesis of both negative-sense genome RNA and positive-sense mRNA species of lymphocytic choriomeningitis virus (LCMV) directed by the human RNA polymerases I and II, respectively, within the same plasmid. This approach reduces by half the number of vectors required for arenavirus rescue, which could facilitate virus rescue in cell lines approved for human vaccine production but that cannot be transfected at high efficiencies. We have shown the feasibility of this approach by rescuing both the Old World prototypic arenavirus LCMV and the live-attenuated vaccine Candid#1 strain of the New World arenavirus Junín. Moreover, we show the feasibility of using these novel strategies for efficient rescue of recombinant tri-segmented both LCMV and Candid#1.

Comprehensive phenotyping will be required to reveal the pleiotropic functions of a gene and to uncover the wider role of genetic loci within diverse biological systems. The challenge will be to devise phenotyping approaches to characterise the thousands of mutants that are being generated as part of international efforts to acquire a mutant for every gene in the mouse genome. In order to acquire robust datasets of broad based phenotypes from mouse mutants it is necessary to design and implement pipelines that incorporate standardised phenotyping platforms that are validated across diverse mouse genetics centres or mouse clinics. We describe here the rationale and methodology behind one phenotyping pipeline, EMPReSSslim, that was designed as part of the work of the EUMORPHIA and EUMODIC consortia, and which exemplifies some of the challenges facing large-scale phenotyping. EMPReSSslim captures a broad range of data on diverse biological systems, from biochemical to physiological amongst others. Data capture and dissemination is pivotal to the operation of large-scale phenotyping pipelines, including the definition of parameters integral to each phenotyping test and the associated ontological descriptions. EMPReSSslim data is displayed within the EuroPhenome database, where a variety of tools are available to allow the user to search for interesting biological or clinical phenotypes.

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license. PMID:27712582

A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

Microbial colony growth can serve as a useful readout in assays for studying complex genetic interactions or the effects of chemical compounds. Although computational tools for acquiring quantitative measurements of microbial colonies have been developed, their utility can be compromised by inflexible input image requirements, non-trivial installation procedures, or complicated operation. Here, we present the Spotsizer software tool for automated colony size measurements in images of robotically arrayed microbial colonies. Spotsizer features a convenient graphical user interface (GUI), has both single-image and batch-processing capabilities, and works with multiple input image formats and different colony grid types. We demonstrate how Spotsizer can be used for high-throughput quantitative analysis of fission yeast growth. The user-friendly Spotsizer tool provides rapid, accurate, and robust quantitative analyses of microbial growth in a high-throughput format. Spotsizer is freely available at https://data.csiro.au/dap/landingpage?pid=csiro:15330 under a proprietary CSIRO license.

While it is true that the modern computer is many orders of magnitude faster than that of yesteryear; this tremendous growth in CPU clock rates is now over. Unfortunately, however, the growth in demand for computational power has not abated; whereas researchers a decade ago could simply wait for computers to get faster, today the only solution to the growing need for more powerful computational resource lies in the exploitation of parallelism. Software parallelization falls generally into two broad categories--"true parallel" and high-throughput computing. This chapter focuses on the latter of these two types of parallelism. With high-throughput computing, users can run many copies of their software at the same time across many different computers. This technique for achieving parallelism is powerful in its ability to provide high degrees of parallelism, yet simple in its conceptual implementation. This chapter covers various patterns of high-throughput computing usage and the skills and techniques necessary to take full advantage of them. By utilizing numerous examples and sample codes and scripts, we hope to provide the reader not only with a deeper understanding of the principles behind high-throughput computing, but also with a set of tools and references that will prove invaluable as she explores software parallelism with her own software applications and research.

TILLING (Targeting Induced Local Lesions in Genomes) is a general reverse-genetic strategy that provides an allelic series of induced point mutations in genes of interest. High-throughput TILLING allows the rapid and low-cost discovery of induced point mutations in populations of chemically mutagenized individuals. As chemical mutagenesis is widely applicable and mutation detection for TILLING is dependent only on sufficient yield of PCR products, TILLING can be applied to most organisms. We have developed TILLING as a service to the Arabidopsis community known as the Arabidopsis TILLING Project (ATP). Our goal is to rapidly deliver allelic series of ethylmethanesulfonate-induced mutations in target 1-kb loci requested by the international research community. In the first year of public operation, ATP has discovered, sequenced, and delivered >1000 mutations in >100 genes ordered by Arabidopsis researchers. The tools and methodologies described here can be adapted to create similar facilities for other organisms.

Feline infectious peritonitis (FIP) is caused by feline coronaviruses (FCoVs) and represents one of the most important lethal infectious diseases of cats. To date, there is no efficacious prevention and treatment, and our limited knowledge on FIP pathogenesis is mainly based on analysis of experiments with field isolates. In a recent study, we reported a promising approach to study FIP pathogenesis using reversegenetics. We generated a set of recombinant FCoVs and investigated their pathogenicity in vivo. The set included the type I FCoV strain Black, a type I FCoV strain Black with restored accessory gene 7b, two chimeric type I/type II FCoVs and the highly pathogenic type II FCoV strain 79-1146. All recombinant FCoVs and the reference strain isolates were found to establish productive infections in cats. While none of the type I FCoVs and chimeric FCoVs induced FIP, the recombinant type II FCoV strain 79-1146 was as pathogenic as the parental isolate. Interestingly, an intact ORF 3c was confirmed to be restored in all viruses (re)isolated from FIP-diseased animals.

Several arenaviruses cause hemorrhagic fever (HF) in humans, and evidence indicates that the worldwide-distributed prototypic arenavirus lymphocytic choriomeningitis virus (LCMV) is a neglected human pathogen of clinical significance. Moreover, arenaviruses pose a biodefense threat. No licensed anti-arenavirus vaccines are available, and current anti-arenavirus therapy is limited to the use of ribavirin, which is only partially effective and is associated with anemia and other side effects. Therefore, it is important to develop effective vaccines and better antiviral drugs to combat the dual threats of naturally occurring and intentionally introduced arenavirus infections. The development of arenavirus reversegenetic systems is allowing investigators to conduct a detailed molecular characterization of the viral cis-acting signals and trans-acting factors that control each of the steps of the arenavirus life cycle, including RNA synthesis, packaging and budding. Knowledge derived from these studies is uncovering potential novel targets for therapeutic intervention, as well as facilitating the establishment of assays to identify and characterize candidate antiviral drugs capable of interfering with specific steps of the virus life cycle. Likewise, the ability to generate predetermined specific mutations within the arenavirus genome and analyze their phenotypic expression would significantly contribute to the elucidation of arenavirus-host interactions, including the basis of their ability to cause severe HF. This, in turn, could lead to the development of novel, potent and safe arenavirus vaccines. PMID:18782590

Several arenaviruses cause hemorrhagic fever (HF) in humans, and evidence indicates that the worldwide-distributed prototypic arenavirus lymphocytic choriomeningitis virus (LCMV) is a neglected human pathogen of clinical significance. Moreover, arenaviruses pose a biodefense threat. No licensed anti-arenavirus vaccines are available, and current anti-arenavirus therapy is limited to the use of ribavirin, which is only partially effective and is associated with anemia and other side effects. Therefore, it is important to develop effective vaccines and better antiviral drugs to combat the dual threats of naturally occurring and intentionally introduced arenavirus infections. The development of arenavirus reversegenetic systems is allowing investigators to conduct a detailed molecular characterization of the viral cis-acting signals and trans-acting factors that control each of the steps of the arenavirus life cycle, including RNA synthesis, packaging and budding. Knowledge derived from these studies is uncovering potential novel targets for therapeutic intervention, as well as facilitating the establishment of assays to identify and characterize candidate antiviral drugs capable of interfering with specific steps of the virus life cycle. Likewise, the ability to generate predetermined specific mutations within the arenavirus genome and analyze their phenotypic expression would significantly contribute to the elucidation of arenavirus-host interactions, including the basis of their ability to cause severe HF. This, in turn, could lead to the development of novel, potent and safe arenavirus vaccines.

We describe the design, fabrication, and use of a radio frequency reflectometer integrated with a microfluidic system, applied to the very high-throughput measurement of micron-scale particles, passing in a microfluidic channel through the sensor region. The device operates as a microfabricated Coulter counter [U.S. Patent No. 2656508 (1953)], similar to a design we have described previously, but here with significantly improved electrode geometry as well as including electronic tuning of the reflectometer; the two improvements yielding an improvement by more than a factor of 10 in the signal to noise and in the diametric discrimination of single particles. We demonstrate the high-throughput discrimination of polystyrene beads with diameters in the 4-10 microm range, achieving diametric resolutions comparable to the intrinsic spread of diameters in the bead distribution, at rates in excess of 15 x 10(6) beads/h.

Targeting-induced local lesions in genomes (TILLING) is a general strategy for identifying induced point mutations that can be applied to almost any organism. Here, we describe the basic methodology for high-throughput TILLING. Gene segments are amplified using fluorescently tagged primers, and products are denatured and reannealed to form heteroduplexes between the mutated sequence and its wild-type counterpart. These heteroduplexes are substrates for cleavage by the endonuclease CEL I. Following cleavage, products are analyzed on denaturing polyacrylamide gels using the LI-COR DNA analyzer system. High-throughput TILLING has been adopted by the Arabidopsis TILLING Project (ATP) to provide allelic series of point mutations for the general Arabidopsis community.

Targeting induced local lesions in genomes (TILLING) is a general strategy for identifying induced point mutations that can be applied to almost any organism. In this chapter, we describe the basic methodology for high-throughput TILLING. Gene segments are amplified using fluorescently tagged primers, and products are denatured and reannealed to form heteroduplexes between the mutated sequence and its wild-type counterpart. These heteroduplexes are substrates for cleavage by the endonuclease CEL I. Following cleavage, products are analyzed on denaturing polyacrylamide gels using the LI-COR DNA analyzer system. High-throughput TILLING has been adopted by the Arabidopsis TILLING Project (ATP) to provide allelic series of point mutations for the general Arabidopsis community.

Genetic engineering of protein-based polymers offers distinct advantages over conventional synthesis of polymers. Microorganisms can synthesize high molecular weight materials, in relatively large quantities, that are inherently stereoregular, monodisperse, and of controlled sequence. In addition, specific secondary and higher order structures are determined by this protein sequence. As a result, scientists can design polymers to have unique structural features found in natural protein materials and functional properties that are inherent in certain peptide sequences. For this reason, genetic engineering principles were used to create a set of artificial genes that encode twelve macromolecules having both alpha-helical and disordered coil protein sequences with the last amino acid being cysteine (cys) or tryptophan (trp). Triblock copolymer sequences having coiled-coil protein ends, A or B, where A and B represent alpha-helical acidic and basic leucine zipper proteins, separated by a water soluble flexible spacer coil protein, C, where C represents ((AG)sb3PEG) sbn (n = 10 or 28), showed reversible physical gelation behavior. This behavior is believed to result from the aggregation of two or more helices that form physical crosslinks with the disordered coil domain retaining solvent and preventing precipitation of the chain. Diffising wave spectroscopy was used to investigate the gelation behavior of ACsb{10}Acys in buffer when environmental conditions such as pH, temperature, and concentration were varied. The dynamic intensity autocorrelation function recorded over time for 5% (w/v) ACsb{10}Acys showed that the protein behaved as a gel at pH 6.7-8.0 and that the melting point was between 40sp°C and 48sp°C. In addition to the triblock results, the incorporation of 5sp',5sp',5sp'-trifluoroleucine (Tfl) in place of leucine (Leu) in the A and B blocks was accomplished by synthesizing proteins in bacterial hosts auxotrophic for Leu. The substitution of Tfl for Leu

This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high-throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high-dimensional neuroinformatic representation index containing O(1000-10,000) discriminating dimensions. The pipeline is based on advanced image analysis coupled to digital knowledge representations in the form of dense atlases of the human brain at gross anatomical scale. We demonstrate the integration of these high-dimensional representations with machine learning methods, which have become the mainstay of other fields of science including genomics as well as social networks. Such high-throughput facilities have the potential to alter the way medical images are stored and utilized in radiological workflows. The neuroinformatics pipeline is used to examine cross-sectional and personalized analyses of neuropsychiatric illnesses in clinical applications as well as longitudinal studies. We demonstrate the use of high-throughput machine learning methods for supporting (i) cross-sectional image analysis to evaluate the health status of individual subjects with respect to the population data, (ii) integration of image and personal medical record non-image information for diagnosis and prognosis.

This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high-throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high-dimensional neuroinformatic representation index containing O(1000–10,000) discriminating dimensions. The pipeline is based on advanced image analysis coupled to digital knowledge representations in the form of dense atlases of the human brain at gross anatomical scale. We demonstrate the integration of these high-dimensional representations with machine learning methods, which have become the mainstay of other fields of science including genomics as well as social networks. Such high-throughput facilities have the potential to alter the way medical images are stored and utilized in radiological workflows. The neuroinformatics pipeline is used to examine cross-sectional and personalized analyses of neuropsychiatric illnesses in clinical applications as well as longitudinal studies. We demonstrate the use of high-throughput machine learning methods for supporting (i) cross-sectional image analysis to evaluate the health status of individual subjects with respect to the population data, (ii) integration of image and personal medical record non-image information for diagnosis and prognosis. PMID:24381556

With the development of genomic research technologies, comparative genome studies among vertebrate species are becoming commonplace for human biomedical research. Fish offer unlimited versatility for biomedical research. Extensive studies are done using these fish models, yielding tens of thousands of specific strains and lines, and the number is increasing every day. Thus, high-throughput sperm cryopreservation is urgently needed to preserve these genetic resources. Although high-throughput processing has been widely applied for sperm cryopreservation in livestock for decades, application in biomedical model fishes is still in the concept-development stage because of the limited sample volumes and the biological characteristics of fish sperm. High-throughput processing in livestock was developed based on advances made in the laboratory and was scaled up for increased processing speed, capability for mass production, and uniformity and quality assurance. Cryopreserved germplasm combined with high-throughput processing constitutes an independent industry encompassing animal breeding, preservation of genetic diversity, and medical research. Currently, there is no specifically engineered system available for high-throughput of cryopreserved germplasm for aquatic species. This review is to discuss the concepts and needs for high-throughput technology for model fishes, propose approaches for technical development, and overview future directions of this approach.

With the development of genomic research technologies, comparative genome studies among vertebrate species are becoming commonplace for human biomedical research. Fish offer unlimited versatility for biomedical research. Extensive studies are done using these fish models, yielding tens of thousands of specific strains and lines, and the number is increasing every day. Thus, high-throughput sperm cryopreservation is urgently needed to preserve these genetic resources. Although high-throughput processing has been widely applied for sperm cryopreservation in livestock for decades, application in biomedical model fishes is still in the concept-development stage because of the limited sample volumes and the biological characteristics of fish sperm. High-throughput processing in livestock was developed based on advances made in the laboratory and was scaled up for increased processing speed, capability for mass production, and uniformity and quality assurance. Cryopreserved germplasm combined with high-throughput processing constitutes an independent industry encompassing animal breeding, preservation of genetic diversity, and medical research. Currently, there is no specifically engineered system available for high-throughput of cryopreserved germplasm for aquatic species. This review is to discuss the concepts and needs for high-throughput technology for model fishes, propose approaches for technical development, and overview future directions of this approach.

Highthroughput biological data need to be processed, analyzed, and interpreted to address problems in life sciences. Bioinformatics, computational biology, and systems biology deal with biological problems using computational methods. Clustering is one of the methods used to gain insight into biological processes, particularly at the genomics level. Clearly, clustering can be used in many areas of biological data analysis. However, this paper presents a review of the current clustering algorithms designed especially for analyzing gene expression data. It is also intended to introduce one of the main problems in bioinformatics - clustering gene expression data - to the operations research community. PMID:23144527

A new High-Throughput Explosive Destruction System is disclosed. The new system is comprised of two side-by-side detonation containment vessels each comprising first and second halves that feed into a single agent treatment vessel. Both detonation containment vessels further comprise a surrounding ventilation facility. Moreover, the detonation containment vessels are designed to separate into two half-shells, wherein one shell can be moved axially away from the fixed, second half for ease of access and loading. The vessels are closed by means of a surrounding, clam-shell type locking seal mechanisms.

Ion channels are involved in a variety of fundamental physiological processes, and their malfunction causes numerous human diseases. Therefore, ion channels represent a class of attractive drug targets and a class of important off-targets for in vitro pharmacological profiling. In the past decades, the rapid progress in developing functional assays and instrumentation has enabled highthroughput screening (HTS) campaigns on an expanding list of channel types. Chronologically, HTS methods for ion channels include the ligand binding assay, flux-based assay, fluorescence-based assay, and automated electrophysiological assay. In this review we summarize the current HTS technologies for different ion channel classes and their applications. PMID:26657056

The distinction between model and nonmodel organisms is becoming increasingly blurred. High-throughput, second-generation sequencing approaches are being applied to organisms based on their interesting ecological, physiological, developmental, or evolutionary properties and not on the depth of genetic information available for them. Here, we illustrate this point using a low-cost, efficient technique to determine the fine-scale phylogenetic relationships among recently diverged populations in a species. This application of restriction site-associated DNA tags (RAD tags) reveals previously unresolved genetic structure and direction of evolution in the pitcher plant mosquito, Wyeomyia smithii, from a southern Appalachian Mountain refugium following recession of the Laurentide Ice Sheet at 22,000–19,000 B.P. The RAD tag method can be used to identify detailed patterns of phylogeography in any organism regardless of existing genomic data, and, more broadly, to identify incipient speciation and genome-wide variation in natural populations in general. PMID:20798348

Metagenome data sets present a qualitatively different assembly problem than traditional single-organism whole-genome shotgun (WGS) assembly. The unique aspects of such projects include the presence of a potentially large number of distinct organisms and their representation in the data set at widely different fractions. In addition, multiple closely related strains could be present, which would be difficult to assemble separately. Failure to take these issues into account can result in poor assemblies that either jumble together different strains or which fail to yield useful results. The DOE Joint Genome Institute has sequenced a number of metagenomic projects and plans to considerably increase this number in the coming year. As a result, the JGI has a need for high-throughput tools and techniques for handling metagenome projects. We present the techniques developed to handle metagenome assemblies in a high-throughput environment. This includes a streamlined assembly wrapper, based on the JGI?s in-house WGS assembler, Jazz. It also includes the selection of sensible defaults targeted for metagenome data sets, as well as quality control automation for cleaning up the raw results. While analysis is ongoing, we will discuss preliminary assessments of the quality of the assembly results (http://fames.jgi-psf.org).

Many people in the semiconductor industry bemoan the high costs of masks and view mask cost as one of the significant barriers to bringing new chip designs to market. All that is needed is a viable maskless technology and the problem will go away. Numerous sites around the world are working on maskless lithography but inevitably, the question asked is "Wouldn't a one wafer per hour maskless tool make a really good mask writer?" Of course, the answer is yes, the hesitation you hear in the answer isn't based on technology concerns, it's financial. The industry needs maskless lithography because mask costs are too high. Mask costs are too high because mask pattern generators (PG's) are slow and expensive. If mask PG's become much faster, mask costs go down, the maskless market goes away and the PG supplier is faced with an even smaller tool demand from the mask shops. Technical success becomes financial suicide - or does it? In this paper we will present the results of a model that examines some of the consequences of introducing highthroughput maskless pattern generation. Specific features in the model include tool throughput for masks and wafers, market segmentation by node for masks and wafers and mask cost as an entry barrier to new chip designs. How does the availability of low cost masks and maskless tools affect the industries tool makeup and what is the ultimate potential market for highthroughput maskless pattern generators?

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions—notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program. PMID:23267079

Exposure to Mycobacterium tuberculosis (Mtb) aerosols is a major threat to tuberculosis (TB) researchers, even in bio-safety level-3 (BSL-3) facilities. Automation and high-throughput screens (HTS) in BSL3 facilities are essential for minimizing manual aerosol-generating interventions and facilitating TB research. In the present study, we report the development and validation of a high-throughput, 24-well ‘spot-assay’ for selecting bactericidal compounds against Mtb. The bactericidal screen concept was first validated in the fast-growing surrogate Mycobacterium smegmatis (Msm) and subsequently confirmed in Mtb using the following reference anti-tubercular drugs: rifampicin, isoniazid, ofloxacin and ethambutol (RIOE, acting on different targets). The potential use of the spot-assay to select bactericidal compounds from a large library was confirmed by screening on Mtb, with parallel plating by the conventional gold standard method (correlation, r2 = 0.808). An automated spot-assay further enabled an MBC90 determination on resistant and sensitive Mtb clinical isolates. The implementation of the spot-assay in kinetic screens to enumerate residual Mtb after either genetic silencing (anti-sense RNA, AS-RNA) or chemical inhibition corroborated its ability to detect cidality. This relatively simple, economical and quantitative HTS considerably minimized the bio-hazard risk and enabled the selection of novel vulnerable Mtb targets and mycobactericidal compounds. Thus, spot-assays have great potential to impact the TB drug discovery process. PMID:25693161

Positional cloning of mutations in model genetic systems is a powerful method for the identification of targets of medical and agricultural importance. To facilitate the high-throughput mapping of mutations in Caenorhabditis elegans, we have identified a further 9602 putative new single nucleotide polymorphisms (SNPs) between two C. elegans strains, Bristol N2 and the Hawaiian mapping strain CB4856, by sequencing inserts from a CB4856 genomic DNA library and using an informatics pipeline to compare sequences with the canonical N2 genomic sequence. When combined with data from other laboratories, our marker set of 17,189 SNPs provides even coverage of the complete worm genome. To date, we have confirmed >1099 evenly spaced SNPs (one every 91 +/- 56 kb) across the six chromosomes and validated the utility of our SNP marker set and new fluorescence polarization-based genotyping methods for systematic and high-throughput identification of genes in C. elegans by cloning several proprietary genes. We illustrate our approach by recombination mapping and confirmation of the mutation in the cloned gene, dpy-18.

Thermoplastic embossing of metallic glasses promises direct imprinting of metal nanostructures using templates. However, embossing high-aspect-ratio nanostructures faces unworkable flow resistance due to friction and non-wetting conditions at the template interface. Herein, we show that these inherent challenges of embossing can be reversed by thermoplastic drawing using templates. The flow resistance not only remains independent of wetting but also decreases with increasing feature aspect-ratio. Arrays of assembled nanotips, nanowires, and nanotubes with aspect-ratios exceeding 1000 can be produced through controlled elongation and fracture of metallic glass structures. In contrast to embossing, the drawing approach generates two sets of nanostructures upon final fracture; one set remains anchored to the metallic glass substrate while the second set is assembled on the template. This method can be readily adapted for high-throughput fabrication and testing of nanoscale tensile specimens, enabling rapid screening of size-effects in mechanical behavior.

High-throughput screening (HTS) techniques have been applied to many research fields nowadays. Robot microarray printing technique and automation microtiter handling technique allows HTS performing in both heterogeneous and homogeneous formats, with minimal sample required for each assay element. In this dissertation, new HTS techniques for enzyme activity analysis were developed. First, patterns of immobilized enzyme on nylon screen were detected by multiplexed capillary system. The imaging resolution is limited by the outer diameter of the capillaries. In order to get finer images, capillaries with smaller outer diameters can be used to form the imaging probe. Application of capillary electrophoresis allows separation of the product from the substrate in the reaction mixture, so that the product doesn't have to have different optical properties with the substrate. UV absorption detection allows almost universal detection for organic molecules. Thus, no modifications of either the substrate or the product molecules are necessary. This technique has the potential to be used in screening of local distribution variations of specific bio-molecules in a tissue or in screening of multiple immobilized catalysts. Another high-throughput screening technique is developed by directly monitoring the light intensity of the immobilized-catalyst surface using a scientific charge-coupled device (CCD). Briefly, the surface of enzyme microarray is focused onto a scientific CCD using an objective lens. By carefully choosing the detection wavelength, generation of product on an enzyme spot can be seen by the CCD. Analyzing the light intensity change over time on an enzyme spot can give information of reaction rate. The same microarray can be used for many times. Thus, high-throughput kinetic studies of hundreds of catalytic reactions are made possible. At last, we studied the fluorescence emission spectra of ADP and obtained the detection limits for ADP under three different

Advances in molecular biological, analytical, and computational technologies are enabling us to systematically investigate the complex molecular processes underlying biological systems. In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network. We aim here to review datamining and modeling approaches for conceptualizing and unraveling the functional relationships implicit in these datasets. Clustering of co-expression profiles allows us to infer shared regulatory inputs and functional pathways. We discuss various aspects of clustering, ranging from distance measures to clustering algorithms and multiple-duster memberships. More advanced analysis aims to infer causal connections between genes directly, i.e., who is regulating whom and how. We discuss several approaches to the problem of reverse engineering of genetic networks, from discrete Boolean networks, to continuous linear and non-linear models. We conclude that the combination of predictive modeling with systematic experimental verification will be required to gain a deeper insight into living organisms, therapeutic targeting, and bioengineering.

A cross-disciplinary high-throughput neutron spectrometer is currently under construction at OPAL, ANSTO's open pool light-water research reactor. The spectrometer is based on the design of a Be-filter spectrometer (FANS) that is operating at the National Institute of Standards research reactor in the USA. The ANSTO filter-spectrometer will be switched in and out with another neutron spectrometer, the triple-axis spectrometer, Taipan. Thus two distinct types of neutron spectrometers will be accessible: one specialised to perform phonon dispersion analysis and the other, the filter-spectrometer, designed specifically to measure vibrational density of states. A summary of the design will be given along with a detailed ray-tracing analysis. Some preliminary results will be presented from the spectrometer.

Aberrant kinase signaling has been implicated in a number of diseases. While kinases have become attractive drug targets, only a small fraction of human protein kinases have validated inhibitors. Screening libraries of compounds against a kinase or kinases of interest is routinely performed during kinase inhibitor development to identify promising scaffolds for a particular target and to identify kinase targets for compounds of interest. Screening of more focused compound libraries may also be conducted in the later stages of inhibitor development to improve potency and optimize selectivity. The dot blot kinase assay is a robust, high-throughput kinase assay that can be used to screen a number of small molecule compounds against one kinase of interest or several kinases. Here, a protocol for a dot blot kinase assay used for measuring insulin receptor kinase activity is presented. This protocol can be readily adapted for use with other protein kinases. PMID:26501904

Membrane proteins play a tremendously important role in cell physiology and serve as a target for an increasing number of drugs. Structural information is key to understanding their function and for developing new strategies for combating disease. However, the complex physical chemistry associated with membrane proteins has made them more difficult to study than their soluble cousins. Electron crystallography has historically been a successful method for solving membrane protein structures and has the advantage of providing the natural environment of a lipid membrane. Specifically, when membrane proteins form two-dimensional arrays within a lipid bilayer, images and diffraction can be recorded by electron microscopy. The corresponding data can be combined to produce a three-dimensional reconstruction which, under favorable conditions, can extend to atomic resolution. Like X-ray crystallography, the quality of the structures are very much dependent on the order and size of the crystals. However, unlike X-ray crystallography, high-throughput methods for screening crystallization trials for electron crystallography are not in general use. In this chapter, we describe two alternative and potentially complementary methods for high-throughput screening of membrane protein crystallization within the lipid bilayer. The first method relies on the conventional use of dialysis for removing detergent and thus reconstituting the bilayer; an array of dialysis wells in the standard 96-well format allows the use of a liquid-handling robot and greatly increases throughput. The second method relies on detergent complexation by cyclodextrin; a specialized pipetting robot has been designed not only to titrate cyclodextrin, but to use light scattering to monitor the reconstitution process. In addition, the use of liquid-handling robots for making negatively stained grids and methods for automatically imaging samples in the electron microscope are described. PMID:23132066

In plant breeding, one of the biggest obstacles in genetic improvement is the lack of proven rapid methods for measuring plant responses in field conditions. Therefore, the major objective of this research was to evaluate the feasibility of utilizing high-throughput remote sensing technology for rapid measurement of phenotyping traits in legume crops. The plant responses of several chickpea and peas varieties to the environment were assessed with an unmanned aerial vehicle (UAV) integrated with multispectral imaging sensors. Our preliminary assessment showed that the vegetation indices are strongly correlated (p<0.05) with seed yield of legume crops. Results endorse the potential of UAS-based sensing technology to rapidly measure those phenotyping traits.

High-throughput screening for genetic analysis, combinatorial chemistry, and clinical diagnostics benefits from multiplexing, which allows for the simultaneous assay of several analytes but necessitates an encoding scheme for molecular identification. Current approaches for multiplexed analysis involve complicated or expensive processes for encoding, functionalizing, or decoding active substrates (particles or surfaces) and often yield a very limited number of analyte-specific codes. We present a method based on continuous-flow lithography that combines particle synthesis and encoding and probe incorporation into a single process to generate multifunctional particles bearing over a million unique codes. By using such particles, we demonstrate a multiplexed, single-fluorescence detection of DNA oligomers with encoded particle libraries that can be scanned rapidly in a flow-through microfluidic channel. Furthermore, we demonstrate with high specificity the same multiplexed detection using individual multiprobe particles.

The genus Fabavirus currently consists of five species represented by viruses that infect a wide range of hosts but none reported from temperate climate fruit trees. A virus with genomic features resembling fabaviruses (tentatively named Prunus virus F, PrVF) was revealed by highthroughput sequencing of extracts from a sweet cherry tree (Prunus avium). PrVF was subsequently shown to be graft transmissible and further identified in three other non-symptomatic Prunus spp. from different geographical locations. Two genetic variants of RNA1 and RNA2 coexisted in the same samples. RNA1 consisted of 6,165 and 6,163 nucleotides, and RNA2 consisted of 3,622 and 3,468 nucleotides.

Advances in our ability to systematically introduce and track controlled genetic variance in microorganisms have, in the past decade, fuelled high-throughputreversegenetics approaches. When coupled to quantitative readouts, such approaches are extremely powerful at elucidating gene function and providing insights into the underlying pathways and the overall cellular network organization. Yet, until now, all efforts to quantify microbial macroscopic phenotypes have been restricted to monitoring growth in a small number of model microorganisms. We have developed an image analysis software named Iris, which allows for systematic exploration of a number of orthogonal-to-growth processes, including biofilm formation, colony morphogenesis, envelope biogenesis, sporulation and reporter activity. In addition, Iris provides more sensitive growth measurements than currently available software and is compatible with a variety of different microorganisms, as well as with endpoint or kinetic data. We used Iris to reanalyse existing chemical genomics data in Escherichia coli and to perform proof-of-principle screens on colony biofilm formation and morphogenesis of different bacterial species and the pathogenic fungus Candida albicans. We thereby recapitulated existing knowledge but also identified a plethora of additional genes and pathways involved in both processes.

Background Behavioral inflexibility is a feature of schizophrenia, attention deficit-hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task. Methods We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2–5 mice/strain, N = 176) for which we have matched data on sequence, gene expression in key CNS regions, and neuroreceptor levels. Results Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (~0.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak LRS at 86.2Mb (p reversal learning phenotype, including Syn3, Nt5dc3 and Hcfc2. Conclusions This work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly-related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology. PMID:21392734

A key aim of the ToxCast project is to investigate modern molecular and genetic high content and highthroughput screening (HTS) assays, along with various computational tools to supplement and perhaps replace traditional assays for evaluating chemical toxicity. Genotoxicity is a...

Implementation of molecular methods in hop breeding is dependent on the availability of sizeable numbers of polymorphic markers and a comprehensive understanding of genetic variation. Diversity Arrays Technology (DArT) is a high-throughput cost-effective method for the discovery of large numbers of...

In the last decades, the basic techniques of microfluidics for the study of cells such as cell culture, cell separation, and cell lysis, have been well developed. Based on cell handling techniques, microfluidics has been widely applied in the field of PCR (Polymerase Chain Reaction), immunoassays, organ-on-chip, stem cell research, and analysis and identification of circulating tumor cells. As a major step in drug discovery, high-throughput screening allows rapid analysis of thousands of chemical, biochemical, genetic or pharmacological tests in parallel. In this review, we summarize the application of microfluidics in cell-based highthroughput screening. The screening methods mentioned in this paper include approaches using the perfusion flow mode, the droplet mode, and the microarray mode. We also discuss the future development of microfluidic based highthroughput screening platform for drug discovery.

As highthroughput screening (HTS) plays a larger role in toxicity testing, camputational toxicology has emerged as a critical component in interpreting the large volume of data produced. Computational models designed to quantify potential adverse effects based on HTS data will benefit from additional data sources that connect the magnitude of perturbation from the in vitro system to a level of concern at the organism or population level. The adverse outcome pathway (AOP) concept provides an ideal framework for combining these complementary data. Recent international efforts under the auspices of the Organization for Economic Co-operation and Development (OECD) have resulted in an AOP wiki designed to house formal descriptions of AOPs suitable for use in regulatory decision making. Recent efforts have built upon this to include an ontology describing the AOP with linkages to biological pathways, physiological terminology, and taxonomic applicability domains. Incorporation of an AOP network tool developed by the U.S. Army Corps of Engineers also allows consideration of cumulative risk from chemical and non-chemical stressors. Biomarkers are an important complement to formal AOP descriptions, particularly when dealing with susceptible subpopulations or lifestages in human health risk assessment. To address the issue of nonchemical stressors than may modify effects of criteria air pollutants, a novel method was used to integrate blood gene expression data with hema

We report a microanalytical method to study enzyme kinetics. The technique involves immobilizing horseradish peroxidase on a poly-L-lysine (PLL)- coated glass slide in a microarray format, followed by applying substrate solution onto the enzyme microarray. Enzyme molecules are immobilized on the PLL-coated glass slide through electrostatic interactions, and no further modification of the enzyme or glass slide is needed. In situ detection of the products generated on the enzyme spots is made possible by monitoring the light intensity of each spot using a scientific-grade charged-coupled device (CCD). Reactions of substrate solutions of various types and concentrations can be carried out sequentially on one enzyme microarray. To account for the loss of enzyme from washing in between runs, a standard substrate solution is used for calibration. Substantially reduced amounts of substrate solution are consumed for each reaction on each enzyme spot. The Michaelis constant K{sub m} obtained by using this method is comparable to the result for homogeneous solutions. Absorbance detection allows universal monitoring, and no chemical modification of the substrate is needed. High-throughput studies of native enzyme kinetics for multiple enzymes are therefore possible in a simple, rapid, and low-cost manner.

EPA has made many recent advances in highthroughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing and screening chemicals. A recent report by the National Research Council of the National Academies, Exposure Science in the 21st Century: A Vision and a Strategy (NRC 2012) laid out a number of applications in chemical evaluation of both toxicity and risk in critical need of quantitative exposure predictions, including screening and prioritization of chemicals for targeted toxicity testing, focused exposure assessments or monitoring studies, and quantification of population vulnerability. Despite these significant needs, for the majority of chemicals (e.g. non-pesticide environmental compounds) there are no or limited estimates of exposure. For example, exposure estimates exist for only 7% of the ToxCast Phase II chemical list. In addition, the data required for generating exposure estimates for large numbers of chemicals is severely lacking (Egeghy et al. 2012). This SAP reviewed the use of EPA's ExpoCast model to rapidly estimate potential chemical exposures for prioritization and screening purposes. The focus was on bounded chemical exposure values for people and the environment for the Endocrine Disruptor Screening Program (EDSP) Universe of Chemicals. In addition to exposure, the SAP

Saccharomyces cerevisiae (budding yeast) is a powerful eukaryotic model organism ideally suited to high-throughputgenetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc) transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids) or genome mutation (e.g., gene mutation, deletion, epitope tagging) is a useful and long established method. However, a reliable and optimized highthroughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in highthroughput molecular and/or genetic analysis of yeast. PMID:28319150

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone. PMID:23748604

Influenza viruses cause annual seasonal epidemics and occasional pandemics of human respiratory disease. Influenza virus infections represent a serious public health and economic problem, which are most effectively prevented through vaccination. However, influenza viruses undergo continual antigenic variation, which requires either the annual reformulation of seasonal influenza vaccines or the rapid generation of vaccines against potential pandemic virus strains. The segmented nature of influenza virus allows for the reassortment between two or more viruses within a co-infected cell, and this characteristic has also been harnessed in the laboratory to generate reassortant viruses for their use as either inactivated or live-attenuated influenza vaccines. With the implementation of plasmid-based reversegenetics techniques, it is now possible to engineer recombinant influenza viruses entirely from full-length complementary DNA copies of the viral genome by transfection of susceptible cells. These reversegenetics systems have provided investigators with novel and powerful approaches to answer important questions about the biology of influenza viruses, including the function of viral proteins, their interaction with cellular host factors and the mechanisms of influenza virus transmission and pathogenesis. In addition, reversegenetics techniques have allowed the generation of recombinant influenza viruses, providing a powerful technology to develop both inactivated and live-attenuated influenza vaccines. In this review, we will summarize the current knowledge of state-of-the-art, plasmid-based, influenza reversegenetics approaches and their implementation to provide rapid, convenient, safe and more effective influenza inactivated or live-attenuated vaccines. PMID:28025504

The complexity of neurons and neuronal circuits in brain tissue requires the genetic manipulation, labeling, and tracking of single cells. However, current methods for manipulating cells in brain tissue are limited to either bulk techniques, lacking single-cell accuracy, or manual methods that provide single-cell accuracy but at significantly lower throughputs and repeatability. Here, we demonstrate high-throughput, efficient, reliable, and combinatorial delivery of multiple genetic vectors and reagents into targeted cells within the same tissue sample with single-cell accuracy. Our system automatically loads nanoliter-scale volumes of reagents into a micropipette from multiwell plates, targets and transfects single cells in brain tissues using a robust electroporation technique, and finally preps the micropipette by automated cleaning for repeating the transfection cycle. We demonstrate multi-colored labeling of adjacent cells, both in organotypic and acute slices, and transfection of plasmids encoding different protein isoforms into neurons within the same brain tissue for analysis of their effects on linear dendritic spine density. Our platform could also be used to rapidly deliver, both ex vivo and in vivo, a variety of genetic vectors, including optogenetic and cell-type specific agents, as well as fast-acting reagents such as labeling dyes, calcium sensors, and voltage sensors to manipulate and track neuronal circuit activity at single-cell resolution. PMID:22536416

Recombinant proteins expressed in animals have been a public concern as a perceived risk to the consumer. Animals are currently being treated with genetically engineered biologicals, such as growth hormone, or fed genetically modified plants. Similarly, various commercially-valuable proteins or pe...

Aquaculture has expanded rapidly to become a major economic and food-producing sector worldwide these last 30 years. In parallel, viral diseases have emerged and rapidly spread from farm to farm causing enormous economic losses. The most problematic viruses encountered in the field are mainly, but not exclusively, RNA viruses belonging to the Novirhabdovirus, Aquabirnavirus, Alphavirus and Betanodavirus genera. The recent establishment of reversegenetics systems to recover infectious fish RNA viruses entirely from cDNA has made possible to genetically manipulate the viral genome. These systems have provided powerful tools to study all aspects of the virus biology and virus-host interactions but also gave the opportunity to use these viruses as live vaccines or as gene vectors. This review provides an overview on the recent breakthroughs achieved by using these reversegenetics systems in terms of viral protein function, virulence and host-specificity factor, vaccine development and vector design. PMID:21314978

Aquaculture has expanded rapidly to become a major economic and food-producing sector worldwide these last 30 years. In parallel, viral diseases have emerged and rapidly spread from farm to farm causing enormous economic losses. The most problematic viruses encountered in the field are mainly, but not exclusively, RNA viruses belonging to the Novirhabdovirus, Aquabirnavirus, Alphavirus and Betanodavirus genera. The recent establishment of reversegenetics systems to recover infectious fish RNA viruses entirely from cDNA has made possible to genetically manipulate the viral genome. These systems have provided powerful tools to study all aspects of the virus biology and virus-host interactions but also gave the opportunity to use these viruses as live vaccines or as gene vectors. This review provides an overview on the recent breakthroughs achieved by using these reversegenetics systems in terms of viral protein function, virulence and host-specificity factor, vaccine development and vector design.

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin–Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin-Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized

DNA damage in the form of abasic sites, chemically altered nucleotides, and strand fragmentation is the foremost limitation in obtaining genetic information from many ancient samples. Upon cell death, DNA continues to endure various chemical attacks such as hydrolysis and oxidation, but repair pathways found in vivo no longer operate. By incubating degraded DNA with specific enzyme combinations adopted from these pathways, it is possible to reverse some of the post-mortem nucleic acid damage prior to downstream analyses such as library preparation, targeted enrichment, and high-throughput sequencing. Here, we evaluate the performance of two available repair protocols on previously characterized DNA extracts from four mammoths. Both methods use endonucleases and glycosylases along with a DNA polymerase-ligase combination. PreCR Repair Mix increases the number of molecules converted to sequencing libraries, leading to an increase in endogenous content and a decrease in cytosine-to-thymine transitions due to cytosine deamination. However, the effects of Nelson Repair Mix on repair of DNA damage remain inconclusive.

The need for increasing productivity in medicinal chemistry and associated improvements in automated synthesis technologies for compound library production during the past few years have resulted in a major challenge for compound purification technology and its organization. To meet this challenge, we have recently set up three full-service chromatography units with the aid of in-house engineers, different HPLC suppliers, and several companies specializing in custom laboratory automation technologies. Our goal was to combine high-throughput purification with the high attention to detail which would be afforded by a dedicated purification service. The resulting final purification laboratory can purify up to 1000 compounds/week in amounts ranging from 5 to 300 mg, whereas the two service intermediate purification units take 100 samples per week from 0.3 to 100 g. The technologies consist of normal-phase and reversed-phase chromatography, robotic fraction pooling and reformatting, a bottling system, an automated external solvent supply and removal system, and a customized, high-capacity freeze-dryer. All work processes are linked by an electronic sample registration and tracking system.

The development of rapid screening and identification techniques is of great importance for drug discovery, doping control, forensic identification, food safety and quality control. Ambient mass spectrometry (AMS) allows rapid and direct analysis of various samples in open air with little sample preparation. Recently, its applications in high-throughput screening have been in rapid progress. During the past decade, various ambient ionization techniques have been developed and applied in high-throughput screening. This review discusses typical applications of AMS, including DESI (desorption electrospray ionization), DART (direct analysis in real time), EESI (extractive electrospray ionization), etc., in high-throughput screening (HTS).

The skin is a highly regenerative organ which plays critical roles in protecting the body and sensing its environment. Consequently, morbidity and mortality associated with skin defects represent a significant health issue. To identify genes important in skin development and homeostasis, we have applied a highthroughput, multi-parameter phenotype screen to the conditional targeted mutant mice generated by the Wellcome Trust Sanger Institute's Mouse Genetics Project (Sanger-MGP). A total of 562 different mouse lines were subjected to a variety of tests assessing cutaneous expression, macroscopic clinical disease, histological change, hair follicle cycling, and aberrant marker expression. Cutaneous lesions were associated with mutations in 23 different genes. Many of these were not previously associated with skin disease in the organ (Mysm1, Vangl1, Trpc4ap, Nom1, Sparc, Farp2, and Prkab1), while others were ascribed new cutaneous functions on the basis of the screening approach (Krt76, Lrig1, Myo5a, Nsun2, and Nf1). The integration of these skin specific screening protocols into the Sanger-MGP primary phenotyping pipelines marks the largest reported reversegenetic screen undertaken in any organ and defines approaches to maximise the productivity of future projects of this nature, while flagging genes for further characterisation.

In the present century sequencing is to the DNA science, what gel electrophoresis was to it in the last century. From 1977 to 2016 three generation of the sequencing technologies of various types have been developed. Second and third generation sequencing technologies referred commonly to as next generation sequencing technology, has evolved significantly with increase in sequencing speed, decrease in sequencing cost, since its inception in 2004. GS FLX by 454 Life Sciences/Roche diagnostics, Genome Analyzer, HiSeq, MiSeq and NextSeq by Illumina, Inc., SOLiD by ABI, Ion Torrent by Life Technologies are various type of the sequencing platforms available for second generation sequencing. The platforms available for the third generation sequencing are Helicos™ Genetic Analysis System by SeqLL, LLC, SMRT Sequencing by Pacific Biosciences, Nanopore sequencing by Oxford Nanopore's, Complete Genomics by Beijing Genomics Institute and GnuBIO by BioRad, to name few. The present article is an overview of the principle and the sequencing chemistry of these highthroughput sequencing technologies along with brief comparison of various types of sequencing platforms available.

A high-throughput (highthroughput is the ability to process large numbers of samples) and companion informatics system has been developed and implemented. Highthroughput is defined as the ability to autonomously evaluate large numbers of samples, while an informatics system provides the software control of the physical devices, in addition to the organization and storage of the generated electronic data. This highthroughput system includes both an ultra-violet and visible light spectrometer (UV-Vis) and a Fourier transform infrared spectrometer (FTIR) integrated with a multi sample positioning table. This method is designed to quantify changes in polymeric materials occurring from controlled temperature, humidity and high flux UV exposures. The integration of the software control of these analytical instruments within a single computer system is presented. Challenges in enhancing the system to include additional analytical devices are discussed. PMID:27366626

Highthroughput exposure screening models can provide quantitative predictions for thousands of chemicals; however these predictions must be systematically evaluated for predictive ability. Without the capability to make quantitative, albeit uncertain, forecasts of exposure, the ...

As highthroughput screening (HTS) approaches play a larger role in toxicity testing, computational toxicology has emerged as a critical component in interpreting the large volume of data produced. Computational models for this purpose are becoming increasingly more sophisticated...

Highthroughput screening (HTS) promises to allow prioritization of thousands of environmental chemicals with little or no in vivo information. For bioactivity identified by HTS, toxicokinetic (TK) models are essential to predict exposure thresholds below which no significant bio...

Highthroughput approaches for quantifying chemical hazard, exposure, and sustainability have the potential to dramatically impact the pace and nature of risk assessments. Integrated evaluation strategies developed at the US EPA incorporate inherency,bioactivity,bioavailability, ...

Highthroughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course...

Background Information on polymorphic DNA in organelle genomes is essential for evolutionary and ecological studies. However, it is challenging to perform high-throughput investigations of chloroplast and mitochondrial DNA polymorphisms. In recent years, EcoTILLING stands out as one of the most universal, low-cost, and high-throughputreversegenetic methods, and the identification of natural genetic variants can provide much information about gene function, association mapping and linkage disequilibrium analysis and species evolution. Until now, no report exists on whether this method is applicable to organelle genomes and to what extent it can be used. Methodology/Principal Findings To address this problem, we adapted the CEL I-based heteroduplex cleavage strategy used in Targeting Induced Local Lesions in Genomes (TILLING) for the discovery of nucleotide polymorphisms in organelle genomes. To assess the applicability and accuracy of this technology, designated ORG-EcoTILLING, at different taxonomic levels, we sampled two sets of taxa representing accessions from the Brassicaceae with three chloroplast genes (accD, matK and rbcL) and one mitochondrial gene (atp6). The method successfully detected nine, six and one mutation sites in the accD, matK and rbcL genes, respectively, in 96 Brassica accessions. These mutations were confirmed by DNA sequencing, with 100% accuracy at both inter- and intraspecific levels. We also detected 44 putative mutations in accD in 91 accessions from 45 species and 29 genera of seven tribes. Compared with DNA sequencing results, the false negative rate was 36%. However, 17 SNPs detected in atp6 were completely identical to the sequencing results. Conclusions/Significance These results suggest that ORG-EcoTILLING is a powerful and cost-effective alternative method for high-throughput genome-wide assessment of inter- and intraspecific chloroplast and mitochondrial DNA polymorphisms. It will play an important role in evolutionary and

Quantitative trait locus (QTL) mapping in plants dates to the 1980’s, but earlier studies were often hindered by the expense and time required to identify large numbers of polymorphic genetic markers that differentiated the parental genotypes and then to genotype them on large segregating mapping po...

Endomembrane cycling processes in plants remain mostly intractable through classical genetic interrogation. Chemical disruption of these processes provides an opportunity to slow or inhibit these processes for study. Tobacco pollen, which is dependent upon endomembrane cycling for tube growth, provides a plant system that is amenable to high-throughput screening of chemical disruptors. We describe here the process that allowed the identification of over 360 endomembrane cycling disruptors.

Zebrafish are an important model organism with inherent advantages that have the potential to make zebrafish a widely applied model for the study of energy homeostasis and obesity. The small size of zebrafish allows for assays on embryos to be conducted in a 96- or 384-well plate format, Morpholino and CRISPR based technologies promote ease of genetic manipulation, and drug treatment by bath application is viable. Moreover, zebrafish are ideal for forward genetic screens allowing for novel gene discovery. Given the relative novelty of zebrafish as a model for obesity, it is necessary to develop tools that fully exploit these benefits. Herein, we describe a method to measure energy expenditure in thousands of embryonic zebrafish simultaneously. We have developed a whole animal microplate platform in which we use 96-well plates to isolate individual fish and we assess cumulative NADH2 production using the commercially available cell culture viability reagent alamarBlue. In poikilotherms the relationship between NADH2 production and energy expenditure is tightly linked. This energy expenditure assay creates the potential to rapidly screen pharmacological or genetic manipulations that directly alter energy expenditure or alter the response to an applied drug (e.g. insulin sensitizers).

Zika virus (ZIKV), a typical example of a re‐emerging pathogen, recently caused large outbreaks in Pacific islands and the Americas, associated with congenital diseases and neurological complications. Deciphering the natural history, ecology and pathophysiology of this mosquito-borne pathogen requires effective reversegenetics tools. In the current study, using the bacterium-free ‘Infectious Subgenomic Amplicons’ (ISA) method, we generated and made available to the scientific community via the non-profit European Virus Archive collection, two simple and performing reversegenetics systems for ZIKV. One is based on an Asian ZIKV strain belonging to the outbreak lineage (French Polynesia 2013). The second was designed from the sequence of a low-passaged ZIKV African strain (Dakar 1984). Using the ISA procedure, we derived wild-type and a variety of specifically engineered ZIKVs in days (intra- and inter-lineage chimeras). Since they are based on low-passaged ZIKV strains, these engineered viruses provide ideal tools to study the effect of genetic changes observed in different evolutionary time-scales of ZIKV as well as pathophysiology of ZIKV infections. PMID:27991555

The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance.

The rapid development of the engineered nanomaterial (ENM) manufacturing industry has accelerated the incorporation of ENMs into a wide variety of consumer products across the globe. Unintentionally or not, some of these ENMs may be introduced into the environment or come into contact with humans or other organisms resulting in unexpected biological effects. It is thus prudent to have rapid and robust analytical metrology in place that can be used to critically assess and/or predict the cytotoxicity, as well as the potential genotoxicity of these ENMs. Many of the traditional genotoxicity test methods [e.g. unscheduled DNA synthesis assay, bacterial reverse mutation (Ames) test, etc.,] for determining the DNA damaging potential of chemical and biological compounds are not suitable for the evaluation of ENMs, due to a variety of methodological issues ranging from potential assay interferences to problems centered on low sample throughput. Recently, a number of sensitive, high-throughput genotoxicity assays/platforms (CometChip assay, flow cytometry/micronucleus assay, flow cytometry/γ-H2AX assay, automated 'Fluorimetric Detection of Alkaline DNA Unwinding' (FADU) assay, ToxTracker reporter assay) have been developed, based on substantial modifications and enhancements of traditional genotoxicity assays. These new assays have been used for the rapid measurement of DNA damage (strand breaks), chromosomal damage (micronuclei) and for detecting upregulated DNA damage signalling pathways resulting from ENM exposures. In this critical review, we describe and discuss the fundamental measurement principles and measurement endpoints of these new assays, as well as the modes of operation, analytical metrics and potential interferences, as applicable to ENM exposures. An unbiased discussion of the major technical advantages and limitations of each assay for evaluating and predicting the genotoxic potential of ENMs is also provided.

In the past decade, combinatorial and highthroughput experimental methods have revolutionized the pharmaceutical industry, allowing researchers to conduct more experiments in a week than was previously possible in a year. Now highthroughput experimentation is rapidly spreading from its origins in the pharmaceutical world to larger industrial research establishments such as GE and DuPont, and even to smaller companies and universities. Consequently, researchers need to know the kinds of problems, desired outcomes, and appropriate patterns for these new strategies. Editor James Cawse's far-reaching study identifies and applies, with specific examples, these important new principles and techniques. Experimental Design for Combinatorial and HighThroughput Materials Development progresses from methods that are now standard, such as gradient arrays, to mathematical developments that are breaking new ground. The former will be particularly useful to researchers entering the field, while the latter should inspire and challenge advanced practitioners. The book's contents are contributed by leading researchers in their respective fields. Chapters include: -HighThroughput Synthetic Approaches for the Investigation of Inorganic Phase Space -Combinatorial Mapping of Polymer Blends Phase Behavior -Split-Plot Designs -Artificial Neural Networks in Catalyst Development -The Monte Carlo Approach to Library Design and Redesign This book also contains over 200 useful charts and drawings. Industrial chemists, chemical engineers, materials scientists, and physicists working in combinatorial and highthroughput chemistry will find James Cawse's study to be an invaluable resource.

Most of our knowledge on learning and memory formation results from extensive studies on a small number of animal species. Although features and cellular pathways of learning and memory are highly similar in this diverse group of species, there are also subtle differences. Closely related species of parasitic wasps display substantial variation in memory dynamics and can be instrumental to understanding both the adaptive benefit of and mechanisms underlying this variation. Parasitic wasps of the genus Nasonia offer excellent opportunities for multidisciplinary research on this topic. Genetic and genomic resources available for Nasonia are unrivaled among parasitic wasps, providing tools for genetic dissection of mechanisms that cause differences in learning. This study presents a robust, high-throughput method for olfactory conditioning of Nasonia using a host encounter as reward. A T-maze olfactometer facilitates high-throughput memory retention testing and employs standardized odors of equal detectability, as quantified by electroantennogram recordings. Using this setup, differences in memory retention between Nasonia species were shown. In both Nasonia vitripennis and Nasonia longicornis, memory was observed up to at least 5 days after a single conditioning trial, whereas Nasonia giraulti lost its memory after 2 days. This difference in learning may be an adaptation to species-specific differences in ecological factors, for example, host preference. The high-throughput methods for conditioning and memory retention testing are essential tools to study both ultimate and proximate factors that cause variation in learning and memory formation in Nasonia and other parasitic wasp species.

The rapid development of genomic technology has made highthroughput genotyping widely accessible but the associated highthroughput phenotyping is now the major limiting factor in genetic analysis of traits. This paper evaluates the use of thermal imaging for the highthroughput field phenotyping of Solanum tuberosum for differences in stomatal behaviour. A large multi-replicated trial of a potato mapping population was used to investigate the consistency in genotypic rankings across different trials and across measurements made at different times of day and on different days. The results confirmed a high degree of consistency between the genotypic rankings based on relative canopy temperature on different occasions. Genotype discrimination was enhanced both through normalising data by expressing genotype temperatures as differences from image means and through the enhanced replication obtained by using overlapping images. A Monte Carlo simulation approach was used to confirm the magnitude of genotypic differences that it is possible to discriminate. The results showed a clear negative association between canopy temperature and final tuber yield for this population, when grown under ample moisture supply. We have therefore established infrared thermography as an easy, rapid and non-destructive screening method for evaluating large population trials for genetic analysis. We also envisage this approach as having great potential for evaluating plant response to stress under field conditions. PMID:23762433

Delivery of exogenous genetic materials across the cell membrane is a powerful and popular research tool for bioengineering. Among conventional non-viral DNA delivery methods, electroporation (EP) is one of the most widely used technologies and is a standard lab procedure in molecular biology. We developed a novel digital microfluidic electroporation system which has higher efficiency of transgene expression and better cell viability than that of conventional EP techniques. We present the successful performance of digital EP system for transformation of various cell lines by investigating effects of the EP conditions such as electric pulse voltage, number, and duration on the cell viability and transfection efficiency in comparison with a conventional bulk EP system. Through the numerical analysis, we have also calculated the electric field distribution around the cells precisely to verify the effect of the electric field on the high efficiency of the digital EP system. Furthermore, the parallelization of the EP processes has been developed to increase the transformation productivity. This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (Grant Number: 2013R1A1A2011956).

An in situ highthroughput method for the detection of H(2)S during fermentation was developed. The method utilizes a redox reaction in which sulfide ion reduces methylene blue, leading to its decolourisation. Incorporation of methylene blue into the fermentation media allows real-time detection of H(2)S during fermentation and the generation of an H(2)S production profile. Kinetic parameters extracted from the H(2)S production profile can be used to characterise genetic factors affecting H(2)S production and differentiate between environmental conditions affecting it. The method, validated here for Saccharomyces cerevisiae, is suited for highthroughput screening purposes by virtue of its simplicity and the ability to detect H(2)S in micro-scale fermentations.

Genomic sequencing has implicated large numbers of genes and de novo mutations as potential disease risk factors. A highthroughput in vivo model system is needed to validate gene associations with pathology. We developed a Drosophila-based functional system to screen candidate disease genes identified from Congenital Heart Disease (CHD) patients. 134 genes were tested in the Drosophila heart using RNAi-based gene silencing. Quantitative analyses of multiple cardiac phenotypes demonstrated essential structural, functional, and developmental roles for more than 70 genes, including a subgroup encoding histone H3K4 modifying proteins. We also demonstrated the use of Drosophila to evaluate cardiac phenotypes resulting from specific, patient-derived alleles of candidate disease genes. We describe the first highthroughput in vivo validation system to screen candidate disease genes identified from patients. This approach has the potential to facilitate development of precision medicine approaches for CHD and other diseases associated with genetic factors.

Microfluidics or Bio-MEMS technology offers significant advantages for performing high-throughput screens and sensitive assays. The ability to correlate single-cell genetic information with cellular phenotypes is of great importance to biology and medicine because it holds the potential to gain insight into disease pathways that is unavailable from ensemble measurements. Previously, we reported two kinds of prototypes for integrated on-chip gene expression profiling at the single-cell level, and the throughput was designed to be 6. In this work, we present a five-layer microfluidic system for parallelized, rapid, quantitative analysis of RNA templates with low abundance at the single-cell level. The microchip contains two multiplexors and one partitioning valve group, and it leverages a matrix (6 × 8) of quantitative reverse transcription polymerase chain reaction (RT-qPCR) units formed by a set of parallel microchannels concurrently controlled by elastomeric pneumatic valves, thereby enabling parallelized handling and processing of biomolecules in a simplified operation procedure. A comprehensive metallic nanofilm with passivation layer is used to run polymerase chain reaction (PCR) temperature cycles. To demonstrate the utility of the approach, artificial synthesized RNA templates (XenoRNA) and mRNA templates from single cells are employed to perform the 48-readout RT-qPCRs. The PCR products are imaged on a fluorescence microscope using a hydrolysis probe/primer set (TaqMan). Fluorescent intensities of passive reference dye and a fluorescein amidite reporter dye are acquired and measured at the end of PCR cycles.

The HighThroughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based highthroughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to highthroughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and highthroughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on highthroughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.

Recent advancements in animal tracking technology and high-throughput sequencing are rapidly changing the questions and scope of research in the biological sciences. The integration of genomic data with high-tech animal instrumentation comes as a natural progression of traditional work in ecological genetics, and we provide a framework for linking the separate data streams from these technologies. Such a merger will elucidate the genetic basis of adaptive behaviors like migration and hibernation and advance our understanding of fundamental ecological and evolutionary processes such as pathogen transmission, population responses to environmental change, and communication in natural populations. PMID:26745372

Recent advancements in animal tracking technology and high-throughput sequencing are rapidly changing the questions and scope of research in the biological sciences. The integration of genomic data with high-tech animal instrumentation comes as a natural progression of traditional work in ecological genetics, and we provide a framework for linking the separate data streams from these technologies. Such a merger will elucidate the genetic basis of adaptive behaviors like migration and hibernation and advance our understanding of fundamental ecological and evolutionary processes such as pathogen transmission, population responses to environmental change, and communication in natural populations.

Highthroughput technologies continue to develop in response to the challenges set by the genome projects. This article discusses how the techniques of both highthroughput screening (HTS) and synthesis can influence research in parasitology. Examples of the use of targeted and phenotype-based HTS using unbiased compound collections are provided. The important issue of identifying the protein target(s) of bioactive compounds is discussed from the synthetic chemist's perspective. This article concludes by reviewing recent examples of successful target identification studies in parasitology.

Advances in highthroughput sequencing technologies and reduction in cost of sequencing have led to exponential growth in highthroughput DNA sequence data. This growth has posed challenges such as storage, retrieval, and transmission of sequencing data. Data compression is used to cope with these challenges. Various methods have been developed to compress genomic and sequencing data. In this article, we present a comprehensive review of compression methods for genome and reads compression. Algorithms are categorized as referential or reference free. Experimental results and comparative analysis of various methods for data compression are presented. Finally, key challenges and research directions in DNA sequence data compression are highlighted.

Droplet microfluidics offers significant advantages for performing high-throughput screens and sensitive assays. Droplets allow sample volumes to be significantly reduced, leading to concomitant reductions in cost. Manipulation and measurement at kilohertz speeds enable up to 10(8) samples to be screened in one day. Compartmentalization in droplets increases assay sensitivity by increasing the effective concentration of rare species and decreasing the time required to reach detection thresholds. Droplet microfluidics combines these powerful features to enable currently inaccessible high-throughput screening applications, including single-cell and single-molecule assays.

When cellular contractile forces are central to pathophysiology, these forces comprise a logical target of therapy. Nevertheless, existing high-throughput screens are limited to upstream signalling intermediates with poorly defined relationships to such a physiological endpoint. Using cellular force as the target, here we report a new screening technology and demonstrate its applications using human airway smooth muscle cells in the context of asthma and Schlemm's canal endothelial cells in the context of glaucoma. This approach identified several drug candidates for both asthma and glaucoma. We attained rates of 1000 compounds per screening day, thus establishing a force-based cellular platform for high-throughput drug discovery. PMID:25953078

Successful implementation of Highthroughput Experimentation (EE) tools has resulted in their increased acceptance as essential tools in chemical, petrochemical and polymer R&D laboratories. This article provides a number of concrete examples of EE systems, which have been designed and successfully implemented in studies, which focus on deriving reaction kinetic data. The implementation of highthroughput EE tools for performing kinetic studies of both catalytic and non-catalytic systems results in a significantly faster acquisition of high-quality kinetic modeling data, required to quantitatively predict the behavior of complex, multistep reactions.

Global food demand, climatic variability and reduced land availability are driving the need for domestication of new crop species. The accelerated domestication of a rice-like Australian dryland polyploid grass, Microlaena stipoides (Poaceae), was targeted using chemical mutagenesis in conjunction with highthroughput sequencing of genes for key domestication traits. While M. stipoides has previously been identified as having potential as a new grain crop for human consumption, only a limited understanding of its genetic diversity and breeding system was available to aid the domestication process. Next generation sequencing of deeply-pooled target amplicons estimated allelic diversity of a selected base population at 14.3 SNP/Mb and identified novel, putatively mutation-induced polymorphisms at about 2.4 mutations/Mb. A 97% lethal dose (LD97) of ethyl methanesulfonate treatment was applied without inducing sterility in this polyploid species. Forward and reversegenetic screens identified beneficial alleles for the domestication trait, seed-shattering. Unique phenotypes observed in the M2 population suggest the potential for rapid accumulation of beneficial traits without recourse to a traditional cross-breeding strategy. This approach may be applicable to other wild species, unlocking their potential as new food, fibre and fuel crops. PMID:24367532

ABSTRACT Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne pathogen that was first reported in China in 2009. Phylogenetic analysis of the viral genome showed that SFTS virus represents a new lineage within the Phlebovirus genus, distinct from the existing sandfly fever and Uukuniemi virus groups, in the family Bunyaviridae. SFTS disease is characterized by gastrointestinal symptoms, chills, joint pain, myalgia, thrombocytopenia, leukocytopenia, and some hemorrhagic manifestations with a case fatality rate of about 2 to 15%. Here we report the development of reversegenetics systems to study STFSV replication and pathogenesis. We developed and optimized functional T7 polymerase-based M- and S-segment minigenome assays, which revealed errors in the published terminal sequences of the S segment of the Hubei 29 strain of SFTSV. We then generated recombinant viruses from cloned cDNAs prepared to the antigenomic RNAs both of the minimally passaged virus (HB29) and of a cell culture-adapted strain designated HB29pp. The growth properties, pattern of viral protein synthesis, and subcellular localization of viral N and NSs proteins of wild-type HB29pp (wtHB29pp) and recombinant HB29pp viruses were indistinguishable. We also show that the viruses fail to shut off host cell polypeptide production. The robust reversegenetics system described will be a valuable tool for the design of therapeutics and the development of killed and attenuated vaccines against this important emerging pathogen. IMPORTANCE SFTSV and related tick-borne phleboviruses such as Heartland virus are emerging viruses shown to cause severe disease in humans in the Far East and the United States, respectively. Study of these novel pathogens would be facilitated by technology to manipulate these viruses in a laboratory setting using reversegenetics. Here, we report the generation of infectious SFTSV from cDNA clones and demonstrate that the behavior of recombinant viruses

Recent advances in the engineering of sequence-specific synthetic nucleases provide enormous opportunities for genetic manipulation of gene expression in order to study their cellular function in vivo. However, current genotyping methods to detect these programmable nuclease-induced insertion/deletion (indel) mutations in targeted human cells are not compatible for high-throughput screening of knockout clones due to inherent limitations and high cost. Here, we describe an efficient method of genotyping clonal CRISPR/Cas9-mediated mutants in a high-throughput manner involving the use of a direct lysis buffer to extract crude genomic DNA straight from cells in culture, and fluorescent PCR coupled with capillary gel electrophoresis. This technique also allows for genotyping of multiplexed gene targeting in a single clone. Overall, this time- and cost-saving technique is able to circumvent the limitations of current genotyping methods and support high-throughput screening of nuclease-induced mutants. PMID:26498861

Saccharomyces cerevisiae has been an important model for studying the molecular mechanisms of aging in eukaryotic cells. However, the laborious and low-throughput methods of current yeast replicative lifespan assays limit their usefulness as a broad genetic screening platform for research on aging. We address this limitation by developing an efficient, high-throughput microfluidic single-cell analysis chip in combination with high-resolution time-lapse microscopy. This innovative design enables, to our knowledge for the first time, the determination of the yeast replicative lifespan in a high-throughput manner. Morphological and phenotypical changes during aging can also be monitored automatically with a much higher throughput than previous microfluidic designs. We demonstrate highly efficient trapping and retention of mother cells, determination of the replicative lifespan, and tracking of yeast cells throughout their entire lifespan. Using the high-resolution and large-scale data generated from the high-throughput yeast aging analysis (HYAA) chips, we investigated particular longevity-related changes in cell morphology and characteristics, including critical cell size, terminal morphology, and protein subcellular localization. In addition, because of the significantly improved retention rate of yeast mother cell, the HYAA-Chip was capable of demonstrating replicative lifespan extension by calorie restriction. PMID:26170317

High-throughput sequencing has been proposed as a method to genotype microsatellites and overcome the four main technical drawbacks of capillary electrophoresis: amplification artifacts, imprecise sizing, length homoplasy, and limited multiplex capability. The objective of this project was to test a high-throughput amplicon sequencing approach to fragment analysis of short tandem repeats and characterize its advantages and disadvantages against traditional capillary electrophoresis. We amplified and sequenced 12 muskrat microsatellite loci from 180 muskrat specimens and analyzed the sequencing data for precision of allele calling, propensity for amplification or sequencing artifacts, and for evidence of length homoplasy. Of the 294 total alleles, we detected by sequencing, only 164 alleles would have been detected by capillary electrophoresis as the remaining 130 alleles (44%) would have been hidden by length homoplasy. The ability to detect a greater number of unique alleles resulted in the ability to resolve greater population genetic structure. The primary advantages of fragment analysis by sequencing are the ability to precisely size fragments, resolve length homoplasy, multiplex many individuals and many loci into a single high-throughput run, and compare data across projects and across laboratories (present and future) with minimal technical calibration. A significant disadvantage of fragment analysis by sequencing is that the method is only practical and cost-effective when performed on batches of several hundred samples with multiple loci. Future work is needed to optimize throughput while minimizing costs and to update existing microsatellite allele calling and analysis programs to accommodate sequence-aware microsatellite data.

Cellular proliferation is fundamental to organism development, tissue renewal, and diverse disease states such as cancer. In vitro measurement of proliferation by high-throughput screening allows rapid characterization of the effects of small-molecule or genetic treatments on primary and established cell lines. Current assays that directly measure the cell cycle are not amenable to high-throughput processing and analysis. Here we report the adaptation of the chemical method for detecting DNA synthesis by 5-ethynyl-2'-deoxyuridine (EdU) incorporation into both high-throughput liquid handling and high-content imaging analysis. We demonstrate that chemical detection of EdU incorporation is effective for high-resolution analysis and quantitation of DNA synthesis by high-content imaging. To validate this assay platform we used treatments of MCF10A cells with media supplements and pharmacological inhibitors that are known to affect cell proliferation. Treatments with specific kinase inhibitors indicate that EGF and serum stimulation employs both the mitogen extracellular kinase (MEK)/extracellular-regulated kinase (ERK) and phosphoinositol-3 kinase (PI3K)/AKT signaling networks. As described here, this method is fast, reliable, and inexpensive and yields robust data that can be easily interpreted.

Upstream processes are rather complex to design and the productivity of cells under suitable cultivation conditions is hard to predict. The method of choice for examining the design space is to execute high-throughput cultivation screenings in micro-scale format. Various predictive in silico models have been developed for many downstream processes, leading to a reduction of time and material costs. This paper presents a combined optimization approach based on high-throughput micro-scale cultivation experiments and chromatography modeling. The overall optimized system must not necessarily be the one with highest product titers, but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli SE1. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for direct product analytics by simple VIS absorption measurements. High-throughput cultivations were carried out in a 48-well format in a BioLector micro-scale cultivation system (m2p-Labs, Germany). The downstream process optimization for a set of randomly picked upstream conditions producing high yields was performed in silico using a chromatography modeling software developed in-house (ChromX). The suggested in silico-optimized operational modes for product capturing were validated subsequently. The overall best system was chosen based on a combination of excellent up- and downstream performance.

The selective perturbation of complex microbial ecosystems to predictably influence outcomes in engineered and industrial environments remains a grand challenge for geomicrobiology. In some industrial ecosystems, such as oil reservoirs, sulfate reducing microorganisms (SRM) produce hydrogen sulfide which is toxic, explosive and corrosive. Current strategies to selectively inhibit sulfidogenesis are based on non-specific biocide treatments, bio-competitive exclusion by alternative electron acceptors or sulfate-analogs which are competitive inhibitors or futile/alternative substrates of the sulfate reduction pathway. Despite the economic cost of sulfidogenesis, there has been minimal exploration of the chemical space of possible inhibitory compounds, and very little work has quantitatively assessed the selectivity of putative souring treatments. We have developed a high-throughput screening strategy to target SRM, quantitatively ranked the selectivity and potency of hundreds of compounds and identified previously unrecognized SRM selective inhibitors and synergistic interactions between inhibitors. Once inhibitor selectivity is defined, high-throughput characterization of microbial community structure across compound gradients and identification of fitness determinants using isolate bar-coded transposon mutant libraries can give insights into the genetic mechanisms whereby compounds structure microbial communities. The high-throughput (HT) approach we present can be readily applied to target SRM in diverse environments and more broadly, could be used to identify and quantify the potency and selectivity of inhibitors of a variety of microbial metabolisms. Our findings and approach are relevant for engineering environmental ecosystems and also to understand the role of natural gradients in shaping microbial niche space.

Saccharomyces cerevisiae has been an important model for studying the molecular mechanisms of aging in eukaryotic cells. However, the laborious and low-throughput methods of current yeast replicative lifespan assays limit their usefulness as a broad genetic screening platform for research on aging. We address this limitation by developing an efficient, high-throughput microfluidic single-cell analysis chip in combination with high-resolution time-lapse microscopy. This innovative design enables, to our knowledge for the first time, the determination of the yeast replicative lifespan in a high-throughput manner. Morphological and phenotypical changes during aging can also be monitored automatically with a much higher throughput than previous microfluidic designs. We demonstrate highly efficient trapping and retention of mother cells, determination of the replicative lifespan, and tracking of yeast cells throughout their entire lifespan. Using the high-resolution and large-scale data generated from the high-throughput yeast aging analysis (HYAA) chips, we investigated particular longevity-related changes in cell morphology and characteristics, including critical cell size, terminal morphology, and protein subcellular localization. In addition, because of the significantly improved retention rate of yeast mother cell, the HYAA-Chip was capable of demonstrating replicative lifespan extension by calorie restriction.

EPA has made many recent advances in highthroughput bioactivity testing. However, concurrent advances in rapid, quantitative prediction of human and ecological exposures have been lacking, despite the clear importance of both measures for a risk-based approach to prioritizing an...

In the ExpoCast project, highthroughput (HT) exposure models enable rapid screening of large numbers of chemicals for exposure potential. Evaluation of these models requires empirical exposure data and due to the paucity of human metabolism/exposure data such evaluations includ...

Understanding health risks to embryonic development from exposure to environmental chemicals is a significant challenge given the diverse chemical landscape and paucity of data for most of these compounds. Highthroughput screening (HTS) in EPA’s ToxCastTM project provides vast d...

High-throughput metabolomic assays that allow simultaneous targeted screening of hundreds of metabolites have recently become available in kit form. Such assays provide a window into understanding changes to biochemical pathways due to chemical exposure or disease, and are usefu...

This poster summarizes efforts of the Chemical Safety for Sustainability's Rapid Exposure and Dosimetry (RED) team to facilitate the development and refinement of toxicokinetics (TK) tools to be used in conjunction with the highthroughput toxicity testing data generated as a par...

High-throughput screening (HTS) studies are providing a rich source of data that can be applied to profile thousands of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition to projects worldwide,...

The use of highthroughput screening (HTS) datasets will need to adequately account for uncertainties in the data generation process and propagate these uncertainties through to ultimate use. Uncertainty arises at multiple levels in the construction of predictors using in vitro ...

Highthroughput screening (HTS) data characterizing chemical-induced biological activity has been generated for thousands of environmentally-relevant chemicals by the US inter-agency Tox21 and the US EPA ToxCast programs. For a limited set of chemicals, bioactive concentrations r...

Medicago truncatula has been widely adopted as a model plant for crop legume species of the Vicieae. Despite the availability of transformation and regeneration protocols, there are currently limited tools available in this species for the systematic investigation of gene function. Within the framework of the European Grain Legumes Integrated Project (http://www.eugrainlegumes.org), chemical mutagenesis was applied to M. truncatula to create two mutant populations that were used to establish a TILLING (targeting induced local lesions in genomes) platform and a phenotypic database, allowing both reverse and forward genetics screens. Both populations had the same M2 line number, but differed in their M1 population size: population 1 was derived from a small M1 population (one-tenth the size of the M2 generation), whereas population 2 was generated by single seed descent and therefore has M1 and M2 generations of equal size. Fifty-six targets were screened, 10 on both populations, and 546 point mutations were identified. Population 2 had a mutation frequency of 1/485 kb, twice that of population 1. The strategy used to generate population 2 is more efficient than that used to generate population 1, with regard to mutagenesis density and mutation recovery. However, the design of population 1 allowed us to estimate the genetically effective cell number to be three in M. truncatula. Phenotyping data to help forward screenings are publicly available, as well as a web tool for ordering seeds at http://www.inra.fr/legumbase.

Since the sequencing of the Arabidopsis thaliana genome in 2000, plant researchers have faced the complex challenge of assigning function to thousands of genes. Functional discovery by in silico prediction or homology search resolved a significant number of genes, but only a minor part has been experimentally validated. Arabidopsis entry into the post-genomic era signified a massive increase in high-throughput approaches to functional discovery, which have since become available through publicly-available web-based resources. The present work focuses on an easy and straightforward strategy that couples data-mining to reversegenetics principles, to allow for the identification of new abiotic stress determinant genes. The strategy explores systematic microarray-based transcriptomics experiments, involving Arabidopsis abiotic stress responses. An overview of the most significant resources and databases for functional discovery in Arabidopsis is presented. The successful application of the outlined strategy is illustrated by the identification of a new abiotic stress determinant gene, HRR, which displays a heat-stress-related phenotype after a loss-of-function reversegenetics approach.

To meet the ever-increasing demand for detection of genetically modified crops (GMCs), low-cost, high-throughput and high-accuracy detection assays are needed. The new multiplex asymmetric polymerase chain reaction and asymmetric hyper-branched rolling circle amplification coupled with reverse dot blot (RDB) systems were developed to detect GMCs. Thirteen oligonucleotide probes were designed to identify endogenous targets (Lec1, Hmg and Sad1), event-specific targets (RRS-5C, RRS-3C, Bt176-3C and MON810-3C), screening targets (35S promoter and NOS terminator), and control targets (18S and PLX). Optimised conditions were as follows: tailed hybridization probes (1-2 pmol/l) were immobilized on a membrane by baking for 2h, and a 10:1 ratio of forward to reverse primers was used. The detection limits were 0.1 μg/l of 2% RRS and 0.5 ng/l of DNA from genetically modified (GM) soybean. These results indicate that the RDB assay could be used to detect multiplex target genes of GMCs rapidly and inexpensively.

Cells have evolved biomolecular networks that process and respond to changing chemical environments. Understanding how complex protein interactions give rise to emergent network properties requires time-resolved analysis of cellular response under a large number of genetic perturbations and chemical environments. To date, the lack of technologies for scalable cell analysis under well-controlled and time-varying conditions has made such global studies either impossible or impractical. To address this need, we have developed a high-throughput microfluidic imaging platform for single-cell studies of network response under hundreds of combined genetic perturbations and time-varying stimulant sequences. Our platform combines programmable on-chip mixing and perfusion with high-throughput image acquisition and processing to perform 256 simultaneous time-lapse live-cell imaging experiments. Nonadherent cells are captured in an array of 2,048 microfluidic cell traps to allow for the imaging of eight different genotypes over 12 h and in response to 32 unique sequences of stimulation, generating a total of 49,000 images per run. Using 12 devices, we carried out >3,000 live-cell imaging experiments to investigate the mating pheromone response in Saccharomyces cerevisiae under combined genetic perturbations and changing environmental conditions. Comprehensive analysis of 11 deletion mutants reveals both distinct thresholds for morphological switching and new dynamic phenotypes that are not observed in static conditions. For example, kss1Delta, fus3Delta, msg5Delta, and ptp2Delta mutants exhibit distinctive stimulus-frequency-dependent signaling phenotypes, implicating their role in filtering and network memory. The combination of parallel microfluidic control with high-throughput imaging provides a powerful tool for systems-level studies of single-cell decision making.

ABSTRACT Certain members of the Arenaviridae family are category A agents capable of causing severe hemorrhagic fevers in humans. Specific antiviral treatments do not exist, and the only commonly used drug, ribavirin, has limited efficacy and can cause severe side effects. The discovery and development of new antivirals are inhibited by the biohazardous nature of the viruses, making them a relatively poorly understood group of human pathogens. We therefore adapted a reverse-genetics minigenome (MG) rescue system based on Junin virus, the causative agent of Argentine hemorrhagic fever, for high-throughput screening (HTS). The MG rescue system recapitulates all stages of the virus life cycle and enables screening of small-molecule libraries under biosafety containment level 2 (BSL2) conditions. The HTS resulted in the identification of four candidate compounds with potent activity against a broad panel of arenaviruses, three of which were completely novel. The target for all 4 compounds was the stage of viral entry, which positions the compounds as potentially important leads for future development. IMPORTANCE The arenavirus family includes several members that are highly pathogenic, causing acute viral hemorrhagic fevers with high mortality rates. No specific effective treatments exist, and although a vaccine is available for Junin virus, the causative agent of Argentine hemorrhagic fever, it is licensed for use only in areas where Argentine hemorrhagic fever is endemic. For these reasons, it is important to identify specific compounds that could be developed as antivirals against these deadly viruses. PMID:26041296

A patterning method termed “RIPPLE” (reactive interface patterning promoted by lithographic electrochemistry) is applied to the fabrication of arrays of dielectric and metallic optical elements. This method uses cyclic voltammetry to impart patterns onto the working electrode of a standard three-electrode electrochemical setup. Using this technique and a template stripping process, periodic arrays of Ag circular Bragg gratings are patterned in a high-throughput fashion over large substrate areas. By varying the scan rate of the cyclically applied voltage ramps, the periodicity of the gratings can be tuned in situ over micrometer and submicrometer length scales. Characterization of the periodic arrays of periodic gratings identified point-like and annular scattering modes at different planes above the structured surface. Facile, reliable, and rapid patterning techniques like RIPPLE may enable the high-throughput and low-cost fabrication of photonic elements and metasurfaces for energy conversion and sensing applications. PMID:25870280

In this study we introduce the starch-recognising carbohydrate binding module family 20 (CBM20) from Aspergillus niger for screening biological variations in starch molecular structure using highthroughput carbohydrate microarray technology. Defined linear, branched and phosphorylated maltooligosaccharides, pure starch samples including a variety of different structures with variations in the amylopectin branching pattern, amylose content and phosphate content, enzymatically modified starches and glycogen were included. Using this technique, different important structures, including amylose content and branching degrees could be differentiated in a highthroughput fashion. The screening method was validated using transgenic barley grain analysed during development and subjected to germination. Typically, extreme branching or linearity were detected less than normal starch structures. The method offers the potential for rapidly analysing resistant and slowly digested dietary starches. PMID:27468930

The rapid evolution of high-throughput theoretical design schemes to discover new lithium battery materials is reviewed, including high-capacity cathodes, low-strain cathodes, anodes, solid state electrolytes, and electrolyte additives. With the development of efficient theoretical methods and inexpensive computers, high-throughput theoretical calculations have played an increasingly important role in the discovery of new materials. With the help of automatic simulation flow, many types of materials can be screened, optimized and designed from a structural database according to specific search criteria. In advanced cell technology, new materials for next generation lithium batteries are of great significance to achieve performance, and some representative criteria are: higher energy density, better safety, and faster charge/discharge speed. Project supported by the National Natural Science Foundation of China (Grant Nos. 11234013 and 51172274) and the National High Technology Research and Development Program of China (Grant No. 2015AA034201).

Over the last few decades, high-throughput (HT) bioscreening, a technique that allows rapid screening of biochemical compound libraries against biological targets, has been widely used in drug discovery, stem cell research, development of new biomaterials, and genomics research. To achieve these ambitions, scaffold-free (or direct) assembly of biological entities of interest has become critical. Appropriate assembling methodologies are required to build an efficient HT bioscreening platform. The development of contact and non-contact assembling systems as a practical solution has been driven by a variety of essential attributes of the bioscreening system, such as miniaturization, highthroughput, and high precision. The present article reviews recent progress on these assembling technologies utilized for the construction of HT bioscreening platforms. PMID:22021162

The resolution of chemically amplified resists is becoming an increasing concern, especially for lithography in the extreme ultraviolet (EUV) regime. Large-scale screening and performance-based down-selection is currently underway to identify resist platforms that can support shrinking feature sizes. Resist screening efforts, however, are hampered by the absence of reliable resolution metrics that can objectively quantify resist resolution in a high-throughput fashion. Here we examine two high-throughput metrics for resist resolution determination. After summarizing their details and justifying their utility, we characterize the sensitivity of both metrics to two of the main experimental uncertainties associated with lithographic exposure tools, namely: limited focus control and limited knowledge of optical aberrations. For an implementation at EUV wavelengths, we report aberration and focus limited error bars in extracted resolution of {approx} 1.25 nm RMS for both metrics making them attractive candidates for future screening and down-selection efforts.

Unbiased, high-throughput screening has proven invaluable for dissecting complex biological processes. Application of this general approach to synaptic function would have a major impact on neuroscience research and drug discovery. However, existing techniques for studying synaptic physiology are labor intensive and low-throughput. Here, we describe a new high-throughput technology for performing assays of synaptic function in primary neurons cultured in microtiter plates. We show that this system can perform 96 synaptic vesicle cycling assays in parallel with high sensitivity, precision, uniformity, and reproducibility and can detect modulators of presynaptic function. By screening libraries of pharmacologically defined compounds on rat forebrain cultures, we have used this system to identify novel effects of compounds on specific aspects of presynaptic function. As a system for unbiased compound as well as genomic screening, this technology has significant applications for basic neuroscience research and for the discovery of novel, mechanism-based treatments for central nervous system disorders. PMID:21998743

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a highthroughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

Population genomics, a new paradigm for population genetics, combine the concepts and techniques of genomics with the theoretical system of population genetics and improve our understanding of microevolution through identification of site-specific effect and genome-wide effects using genome-wide polymorphic sites genotypeing. With the appearance and improvement of the next generation high-throughput sequencing technology, the numbers of plant species with complete genome sequences increased rapidly and large scale resequencing has also been carried out in recent years. Parallel sequencing has also been done in some plant species without complete genome sequences. These studies have greatly promoted the development of population genomics and deepened our understanding of the genetic diversity, level of linking disequilibium, selection effect, demographical history and molecular mechanism of complex traits of relevant plant population at a genomic level. In this review, I briely introduced the concept and research methods of population genomics and summarized the research progress of plant population genomics based on high-throughput sequencing. I also discussed the prospect as well as existing problems of plant population genomics in order to provide references for related studies.

Congenital heart diseases (CHD) represent the most common birth defect in human. The majority of cases are caused by a combination of complex genetic alterations and environmental influences. In the past, many disease-causing mutations have been identified; however, there is still a large proportion of cardiac malformations with unknown precise origin. High-throughput sequencing technologies established during the last years offer novel opportunities to further study the genetic background underlying the disease. In this review, we provide a roadmap for designing and analyzing high-throughput sequencing studies focused on CHD, but also with general applicability to other complex diseases. The three main next-generation sequencing (NGS) platforms including their particular advantages and disadvantages are presented. To identify potentially disease-related genomic variations and genes, different filtering steps and gene prioritization strategies are discussed. In addition, available control datasets based on NGS are summarized. Finally, we provide an overview of current studies already using NGS technologies and showing that these techniques will help to further unravel the complex genetics underlying CHD.

A central challenge in the field of metabolic engineering is the efficient identification of a metabolic pathway genotype that maximizes specific productivity over a robust range of process conditions. Here we review current methods for optimizing specific productivity of metabolic pathways in living cells. New tools for library generation, computational analysis of pathway sequence-flux space, and high-throughput screening and selection techniques are discussed. PMID:27453919

Nuclear Magnetic Resonance (NMR) is a non-contact, powerful structure-elucidation technique for biochemical analysis. NMR spectroscopy is used extensively in a variety of life science applications including drug discovery. However, existing NMR technology is limited in that it cannot run a large number of experiments simultaneously in one unit. Recent advances in micro-fabrication technologies have attracted the attention of researchers to overcome these limitations and significantly accelerate the drug discovery process by developing the next generation of high-throughput NMR spectrometers using Complementary Metal Oxide Semiconductor (CMOS). In this paper, we examine this paradigm shift and explore new design strategies for the development of the next generation of high-throughput NMR spectrometers using CMOS technology. A CMOS NMR system consists of an array of high sensitivity micro-coils integrated with interfacing radio-frequency circuits on the same chip. Herein, we first discuss the key challenges and recent advances in the field of CMOS NMR technology, and then a new design strategy is put forward for the design and implementation of highly sensitive and high-throughput CMOS NMR spectrometers. We thereafter discuss the functionality and applicability of the proposed techniques by demonstrating the results. For microelectronic researchers starting to work in the field of CMOS NMR technology, this paper serves as a tutorial with comprehensive review of state-of-the-art technologies and their performance levels. Based on these levels, the CMOS NMR approach offers unique advantages for high resolution, time-sensitive and high-throughput bimolecular analysis required in a variety of life science applications including drug discovery.

Nuclear Magnetic Resonance (NMR) is a non-contact, powerful structure-elucidation technique for biochemical analysis. NMR spectroscopy is used extensively in a variety of life science applications including drug discovery. However, existing NMR technology is limited in that it cannot run a large number of experiments simultaneously in one unit. Recent advances in micro-fabrication technologies have attracted the attention of researchers to overcome these limitations and significantly accelerate the drug discovery process by developing the next generation of high-throughput NMR spectrometers using Complementary Metal Oxide Semiconductor (CMOS). In this paper, we examine this paradigm shift and explore new design strategies for the development of the next generation of high-throughput NMR spectrometers using CMOS technology. A CMOS NMR system consists of an array of high sensitivity micro-coils integrated with interfacing radio-frequency circuits on the same chip. Herein, we first discuss the key challenges and recent advances in the field of CMOS NMR technology, and then a new design strategy is put forward for the design and implementation of highly sensitive and high-throughput CMOS NMR spectrometers. We thereafter discuss the functionality and applicability of the proposed techniques by demonstrating the results. For microelectronic researchers starting to work in the field of CMOS NMR technology, this paper serves as a tutorial with comprehensive review of state-of-the-art technologies and their performance levels. Based on these levels, the CMOS NMR approach offers unique advantages for high resolution, time-sensitive and high-throughput bimolecular analysis required in a variety of life science applications including drug discovery. PMID:27294925

Enantiopure sulfoxides are prevalent in drugs and are useful chiral auxiliaries in organic synthesis. The biocatalytic enantioselective oxidation of prochiral sulfides is a direct and economical approach for the synthesis of optically pure sulfoxides. The selection of suitable biocatalysts requires rapid and reliable high-throughput screening methods. Here we present four different methods for detecting sulfoxides produced via whole-cell biocatalysis, three of which were exploited for high-throughput screening. Fluorescence detection based on the acid activation of omeprazole was utilized for high-throughput screening of mutant libraries of toluene monooxygenases, but no active variants have been discovered yet. The second method is based on the reduction of sulfoxides to sulfides, with the coupled release and measurement of iodine. The availability of solvent-resistant microtiter plates enabled us to modify the method to a high-throughput format. The third method, selective inhibition of horse liver alcohol dehydrogenase, was used to rapidly screen highly active and/or enantioselective variants at position V106 of toluene ortho-monooxygenase in a saturation mutagenesis library, using methyl-p-tolyl sulfide as the substrate. A success rate of 89% (i.e., 11% false positives) was obtained, and two new mutants were selected. The fourth method is based on the colorimetric detection of adrenochrome, a back-titration procedure which measures the concentration of the periodate-sensitive sulfide. Due to low sensitivity during whole-cell screening, this method was found to be useful only for determining the presence or absence of sulfoxide in the reaction. The methods described in the present work are simple and inexpensive and do not require special equipment. PMID:19465532

Highthroughput robotic systems have been used since the 1990s to carry out biochemical assays in microtiter plates. However, before the application of such systems in industrial fermentation process development, some important specific demands should be taken into account. These are sufficient oxygen supply, optimal growth temperature, minimized sample evaporation, avoidance of contaminations, and simple but reliable process monitoring. A fully automated solution where all these aspects have been taken into account is presented.

Molecular barcoding is an essential tool to use the highthroughput of next generation sequencing platforms optimally in studies involving more than one sample. Various barcoding strategies allow for the incorporation of short recognition sequences (barcodes) into sequencing libraries, either by ligation or polymerase chain reaction (PCR). Here, we present two approaches optimized for generating barcoded sequencing libraries from low copy number extracts and amplification products typical of ancient DNA studies.

Although gene-gene interaction, or epistasis, plays a large role in complex traits in model organisms, genome-wide by genome-wide searches for two-way interaction have limited power in human studies. We thus used knowledge of a biological pathway in order to identify a contribution of epistasis to autism spectrum disorders (ASDs) in humans, a reverse-pathway genetic approach. Based on previous observation of increased ASD symptoms in Mendelian disorders of the Ras/MAPK pathway (RASopathies), we showed that common SNPs in RASopathy genes show enrichment for association signal in GWAS (P = 0.02). We then screened genome-wide for interactors with RASopathy gene SNPs and showed strong enrichment in ASD-affected individuals (P < 2.2 x 10−16), with a number of pairwise interactions meeting genome-wide criteria for significance. Finally, we utilized quantitative measures of ASD symptoms in RASopathy-affected individuals to perform modifier mapping via GWAS. One top region overlapped between these independent approaches, and we showed dysregulation of a gene in this region, GPR141, in a RASopathy neural cell line. We thus used orthogonal approaches to provide strong evidence for a contribution of epistasis to ASDs, confirm a role for the Ras/MAPK pathway in idiopathic ASDs, and to identify a convergent candidate gene that may interact with the Ras/MAPK pathway. PMID:28076348

Human respiratory syncytial virus (RSV) is an enveloped, nonsegmented negative-strand RNA virus of family Paramyxoviridae. RSV is the most complex member of the family in terms of the number of genes and proteins. It is also relatively divergent and distinct from the prototype members of the family. In the past 30 years, we have seen a tremendous increase in our understanding of the molecular biology of RSV based on a succession of advances involving molecular cloning, reversegenetics, and detailed studies of protein function and structure. Much remains to be learned. RSV disease is complex and variable, and the host and viral factors that determine tropism and disease are poorly understood. RSV is notable for a historic vaccine failure in the 1960s involving a formalin-inactivated vaccine that primed for enhanced disease in RSV naïve recipients. Live vaccine candidates have been shown to be free of this complication. However, development of subunit or other protein-based vaccines for pediatric use is hampered by the possibility of enhanced disease and the difficulty of reliably demonstrating its absence in preclinical studies.

Human metapneumovirus (HMPV) was first described in 2001 and has quickly become recognized as an important cause of respiratory tract disease worldwide, especially in the pediatric population. A vaccine against HMPV is required to prevent severe disease associated with infection in infancy. The primary strategy is to develop a live-attenuated virus for intranasal immunization, which is particularly well suited against a respiratory virus. Reversegenetics provides a means of developing highly characterized 'designer' attenuated vaccine candidates. To date, several promising vaccine candidates have been developed, each using a different mode of attenuation. One candidate involves deletion of the G glycoprotein, providing attenuation that is probably based on reduced efficiency of attachment. A second candidate involves deletion of the M2-2 protein, which participates in regulating RNA synthesis and whose deletion has the advantageous property of upregulating transcription and increasing antigen synthesis. A third candidate involves replacing the P protein gene of HMPV with its counterpart from the related avian metapneumovirus, thereby introducing attenuation owing to its chimeric nature and host range restriction. Another live vaccine strategy involves using an attenuated parainfluenza virus as a vector to express HMPV protective antigens, providing a bivalent pediatric vaccine. Additional modifications to provide improved vaccines will also be discussed.

Engineered transcription activator–like effector nucleases (TALENs) have shown promise as facile and broadly applicable genome editing tools. However, no publicly available high-throughput method for constructing TALENs has been published, and large-scale assessments of the success rate and targeting range of the technology remain lacking. Here we describe the fast ligation-based automatable solid-phase high-throughput (FLASH) system, a rapid and cost-effective method for large-scale assembly of TALENs. We tested 48 FLASH-assembled TALEN pairs in a human cell–based EGFP reporter system and found that all 48 possessed efficient gene-modification activities. We also used FLASH to assemble TALENs for 96 endogenous human genes implicated in cancer and/or epigenetic regulation and found that 84 pairs were able to efficiently introduce targeted alterations. Our results establish the robustness of TALEN technology and demonstrate that FLASH facilitates high-throughput genome editing at a scale not currently possible with other genome modification technologies.

Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to highthroughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of highthroughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of highthroughput sequencing data that is pre-packaged for use with the MEGARes database. PMID:27899569

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as 'Minimum Information About a Microarray Experiment' (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/.

Pipetting and dilution are universal processes used in chemical and biological laboratories to assay and experiment. In microfluidics such operations are equally in demand, but difficult to implement. Recently, droplet-based microfluidics has emerged as an exciting new platform for high-throughput experimentation. However, it is challenging to vary the concentration of droplets rapidly and controllably. To this end, we developed a dilution module for high-throughput screening using droplet-based microfluidics. Briefly, a nanolitre-sized sample droplet of defined concentration is trapped within a microfluidic chamber. Through a process of droplet merging, mixing and re-splitting, this droplet is combined with a series of smaller buffer droplets to generate a sequence of output droplets that define a digital concentration gradient. Importantly, the formed droplets can be merged with other reagent droplets to enable rapid chemical and biological screens. As a proof of concept, we used the dilutor to perform a high-throughput homogeneous DNA-binding assay using only nanolitres of sample.

Pipetting and dilution are universal processes used in chemical and biological laboratories to assay and experiment. In microfluidics such operations are equally in demand, but difficult to implement. Recently, droplet-based microfluidics has emerged as an exciting new platform for high-throughput experimentation. However, it is challenging to vary the concentration of droplets rapidly and controllably. To this end, we developed a dilution module for high-throughput screening using droplet-based microfluidics. Briefly, a nanolitre-sized sample droplet of defined concentration is trapped within a microfluidic chamber. Through a process of droplet merging, mixing and re-splitting, this droplet is combined with a series of smaller buffer droplets to generate a sequence of output droplets that define a digital concentration gradient. Importantly, the formed droplets can be merged with other reagent droplets to enable rapid chemical and biological screens. As a proof of concept, we used the dilutor to perform a high-throughput homogeneous DNA-binding assay using only nanolitres of sample.

Legionella pneumophila is a Gram-negative opportunistic human pathogen that causes a severe pneumonia known as Legionnaires' disease. Notably, in the human host, the organism is believed to replicate solely within an intracellular compartment, predominantly within pulmonary macrophages. Consequently, successful therapy is predicated on antimicrobials penetrating into this intracellular growth niche. However, standard antimicrobial susceptibility testing methods test solely for extracellular growth inhibition. Here, we make use of a high-throughput assay to characterize intracellular growth inhibition activity of known antimicrobials. For select antimicrobials, high-resolution dose-response analysis was then performed to characterize and compare activity levels in both macrophage infection and axenic growth assays. Results support the superiority of several classes of nonpolar antimicrobials in abrogating intracellular growth. Importantly, our assay results show excellent correlations with prior clinical observations of antimicrobial efficacy. Furthermore, we also show the applicability of high-throughput automation to two- and three-dimensional synergy testing. High-resolution isocontour isobolograms provide in vitro support for specific combination antimicrobial therapy. Taken together, findings suggest that high-throughput screening technology may be successfully applied to identify and characterize antimicrobials that target bacterial pathogens that make use of an intracellular growth niche. PMID:26392509

Highthroughput screening assays aim to identify small molecules that interfere with protein function, activity, or conformation, which can serve as effective tools for chemical biology studies of targets involved in physiological processes or pathways of interest or disease models, as well as templates for development of therapeutics in medicinal chemistry. Fluorescent biosensors constitute attractive and powerful tools for drug discovery programs, from highthroughput screening assays, to postscreen characterization of hits, optimization of lead compounds, and preclinical evaluation of candidate drugs. They provide a means of screening for inhibitors that selectively target enzymatic activity, conformation, and/or function in vitro. Moreover, fluorescent biosensors constitute useful tools for cell- and image-based, multiplex and multiparametric, high-content screening. Application of fluorescence-based sensors to screen large and complex libraries of compounds in vitro, in cell-based formats or whole organisms requires several levels of optimization to establish robust and reproducible assays. In this review, we describe the different fluorescent biosensor technologies which have been applied to highthroughput screens, and discuss the prerequisite criteria underlying their successful application. Special emphasis is placed on protein kinase biosensors, since these enzymes constitute one of the most important classes of therapeutic targets in drug discovery.

Traditional fermented food is not only the staple food for most of developing countries but also the key healthy food for developed countries. As the healthy function of these foods are gradually discovered, more and more highthroughput biotechnologies are being used to promote the old and new industry. As a result, the microflora, manufacturing processes and product healthy function of these foods were pushed forward either in the respect of profundity or extensiveness nowadays. The application and progress of the highthroughput biotechnologies into traditional fermented food industries were different from each other, which was reviewed and detailed by the catalogues of fermented milk products (yogurt, cheese), fermented sausages, fermented vegetables (kimchi, sauerkraut), fermented cereals (sourdough) and fermented beans (tempeh, natto). Given the further promotion by highthroughput biotechnologies, the middle and/or down-stream process of traditional fermented foods would be optimized and the process of industrialization of local traditional fermented food having many functional factors but in small quantity would be accelerated. The article presents some promising patents on traditional fermented food industry.

In recent years, the food industry has made progress in improving safety testing methods focused on microbial contaminants in order to promote food safety. However, food industry toxicologists must also assess the safety of food-relevant chemicals including pesticides, direct additives, and food contact substances. With the rapidly growing use of new food additives, as well as innovation in food contact substance development, an interest in exploring the use of high-throughput chemical safety testing approaches has emerged. Currently, the field of toxicology is undergoing a paradigm shift in how chemical hazards can be evaluated. Since there are tens of thousands of chemicals in use, many of which have little to no hazard information and there are limited resources (namely time and money) for testing these chemicals, it is necessary to prioritize which chemicals require further safety testing to better protect human health. Advances in biochemistry and computational toxicology have paved the way for animal-free (in vitro) high-throughput screening which can characterize chemical interactions with highly specific biological processes. Screening approaches are not novel; in fact, quantitative high-throughput screening (qHTS) methods that incorporate dose-response evaluation have been widely used in the pharmaceutical industry. For toxicological evaluation and prioritization, it is the throughput as well as the cost- and time-efficient nature of qHTS that makes it

Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to highthroughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of highthroughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of highthroughput sequencing data that is pre-packaged for use with the MEGARes database.

The charophyte green algae (CGA, Streptophyta, Viridiplantae) occupy a key phylogenetic position as the immediate ancestors of land plants but, paradoxically, are less well-studied than the other major plant lineages. This is particularly true in the context of functional genomic studies, where the lack of an efficient protocol for their stable genetic transformation has been a major obstacle. Observations of extant CGA species suggest the existence of some of the evolutionary adaptations that had to occur for land colonization; however, to date, there has been no robust experimental platform to address this genetically. We present a protocol for high-throughput Agrobacterium tumefaciens-mediated transformation of Penium margaritaceum, a unicellular CGA species. The versatility of Penium as a model for studying various aspects of plant cell biology and development was illustrated through non-invasive visualization of protein localization and dynamics in living cells. In addition, the utility of RNA interference (RNAi) for reversegenetic studies was demonstrated by targeting genes associated with cell wall modification (pectin methylesterase) and biosynthesis (cellulose synthase). This provided evidence supporting current models of cell wall assembly and inter-polymer interactions that were based on studies of land plants, but in this case using direct observation in vivo. This new functional genomics platform has broad potential applications, including studies of plant organismal biology and the evolutionary innovations required for transition from aquatic to terrestrial habitats.

Single-channel optical density measurements of population growth are the dominant large scale phenotyping methodology for bridging the gene-function gap in yeast. However, a substantial amount of the genetic variation induced by single allele, single gene or double gene knock-out technologies fail to manifest in detectable growth phenotypes under conditions readily testable in the laboratory. Thus, new high-throughput phenotyping technologies capable of providing information about molecular level consequences of genetic variation are sorely needed. Here we report a protocol for high-throughput Fourier transform infrared spectroscopy (FTIR) measuring biochemical fingerprints of yeast strains. It includes high-throughput cultivation for FTIR spectroscopy, FTIR measurements and spectral pre-treatment to increase measurement accuracy. We demonstrate its capacity to distinguish not only yeast genera, species and populations, but also strains that differ only by a single gene, its excellent signal-to-noise ratio and its relative robustness to measurement bias. Finally, we illustrated its applicability by determining the FTIR signatures of all viable Saccharomyces cerevisiae single gene knock-outs corresponding to lipid biosynthesis genes. Many of the examined knock-out strains showed distinct, highly reproducible FTIR phenotypes despite having no detectable growth phenotype. These phenotypes were confirmed by conventional lipid analysis and could be linked to specific changes in lipid composition. We conclude that the introduced protocol is robust to noise and bias, possible to apply on a very large scale, and capable of generating biologically meaningful biochemical fingerprints that are strain specific, even when strains lack detectable growth phenotypes. Thus, it has a substantial potential for application in the molecular functionalization of the yeast genome.

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based highthroughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution. PMID:28220807

Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30-100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5-1 m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 × 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency.

Animal motility varies with genotype, disease progression, aging, and environmental conditions. In many studies, it is desirable to carry out highthroughput motility-based sorting to isolate rare animals for, among other things, forward genetic screens to identify genetic pathways that regulate phenotypes of interest. Many commonly used screening processes are labor-intensive, lack sensitivity, and require extensive investigator training. Here, we describe a sensitive, highthroughput, automated, motility-based method for sorting nematodes. Our method was implemented in a simple microfluidic device capable of sorting many thousands of animals per hour per module, and is amenable to parallelism. The device successfully enriched for known C. elegans motility mutants. Furthermore, using this device, we isolated low-abundance mutants capable of suppressing the somnogenic effects of the flp-13 gene, which regulates sleep-like quiescence in C. elegans. Subsequent genomic sequencing led to the identification of a flp-13-suppressor gene. This research was supported, in part, by NIH NIA Grant 5R03AG042690-02.

Highthroughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound's highthroughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data.

Remote sensing (RS) of plant canopies permits non-intrusive, high-throughput monitoring of plant physiological characteristics. This study compared three RS approaches using a low flying UAV (unmanned aerial vehicle), with that of proximal sensing, and satellite-based imagery. Two physiological traits were considered, canopy temperature (CT) and a vegetation index (NDVI), to determine the most viable approaches for large scale crop genetic improvement. The UAV-based platform achieves plot-level resolution while measuring several hundred plots in one mission via high-resolution thermal and multispectral imagery measured at altitudes of 30–100 m. The satellite measures multispectral imagery from an altitude of 770 km. Information was compared with proximal measurements using IR thermometers and an NDVI sensor at a distance of 0.5–1 m above plots. For robust comparisons, CT and NDVI were assessed on panels of elite cultivars under irrigated and drought conditions, in different thermal regimes, and on un-adapted genetic resources under water deficit. Correlations between airborne data and yield/biomass at maturity were generally higher than equivalent proximal correlations. NDVI was derived from high-resolution satellite imagery for only larger sized plots (8.5 × 2.4 m) due to restricted pixel density. Results support use of UAV-based RS techniques for high-throughput phenotyping for both precision and efficiency. PMID:27536304

The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice.

Highthroughput mRNA expression profiling can be used to characterize the response of cell culture models to perturbations such as pharmacologic modulators and genetic perturbations. As profiling campaigns expand in scope, it is important to homogenize, summarize, and analyze the resulting data in a manner that captures significant biological signals in spite of various noise sources such as batch effects and stochastic variation. We used the L1000 platform for large-scale profiling of 978 representative genes across thousands of compound treatments. Here, a method is described that uses deep learning techniques to convert the expression changes of the landmark genes into a perturbation barcode that reveals important features of the underlying data, performing better than the raw data in revealing important biological insights. The barcode captures compound structure and target information, and predicts a compound’s highthroughput screening promiscuity, to a higher degree than the original data measurements, indicating that the approach uncovers underlying factors of the expression data that are otherwise entangled or masked by noise. Furthermore, we demonstrate that visualizations derived from the perturbation barcode can be used to more sensitively assign functions to unknown compounds through a guilt-by-association approach, which we use to predict and experimentally validate the activity of compounds on the MAPK pathway. The demonstrated application of deep metric learning to large-scale chemical genetics projects highlights the utility of this and related approaches to the extraction of insights and testable hypotheses from big, sometimes noisy data. PMID:28182661

Iron has been widely studied in nearly every realm of biology. However, current methodologies, such as genetic mapping or mutation screening, have been difficult to apply due to the lack of robust high-throughput methods for quantifying iron levels from cells or tissues. The measurement of total iron levels in tissues, usually done with atomic absorption spectroscopy, is impractical for large numbers of samples and includes the contribution of heme iron from hemoglobin contained in red blood cells. The measurement of non-heme iron by reaction with a bathophenanthroline reagent, a commonly used assay reported more than 30 years ago, is also not feasible for large-scale analyses because it is cuvette-based. We therefore have modified this method to a microplate format that will facilitate large-scale analysis. The microplate assay is highly sensitive and specific, and is a simple and effective method for the measurement of non-heme iron for animal tissues that will enable the application of high-throughput of genetic methodologies.

A shift in toxicity testing from in vivo to in vitro may efficiently prioritize compounds, reveal new mechanisms, and enable predictive modeling. Quantitative high-throughput screening (qHTS) is a major source of data for computational toxicology, and our goal in this study was to aid in the development of predictive in vitro models of chemical-induced toxicity, anchored on interindividual genetic variability. Eighty-one human lymphoblast cell lines from 27 Centre d'Etude du Polymorphisme Humain trios were exposed to 240 chemical substances (12 concentrations, 0.26nM-46.0μM) and evaluated for cytotoxicity and apoptosis. qHTS screening in the genetically defined population produced robust and reproducible results, which allowed for cross-compound, cross-assay, and cross-individual comparisons. Some compounds were cytotoxic to all cell types at similar concentrations, whereas others exhibited interindividual differences in cytotoxicity. Specifically, the qHTS in a population-based human in vitro model system has several unique aspects that are of utility for toxicity testing, chemical prioritization, and high-throughput risk assessment. First, standardized and high-quality concentration-response profiling, with reproducibility confirmed by comparison with previous experiments, enables prioritization of chemicals for variability in interindividual range in cytotoxicity. Second, genome-wide association analysis of cytotoxicity phenotypes allows exploration of the potential genetic determinants of interindividual variability in toxicity. Furthermore, highly significant associations identified through the analysis of population-level correlations between basal gene expression variability and chemical-induced toxicity suggest plausible mode of action hypotheses for follow-up analyses. We conclude that as the improved resolution of genetic profiling can now be matched with high-quality in vitro screening data, the evaluation of the toxicity pathways and the effects of

Seed storage compounds are of crucial importance for human diet, feed and industrial uses. In oleo-proteaginous species like rapeseed, seed oil and protein are the qualitative determinants that conferred economic value to the harvested seed. To date, although the biosynthesis pathways of oil and storage protein are rather well-known, the factors that determine how these types of reserves are partitioned in seeds have to be identified. With the aim of implementing a quantitative genetics approach, requiring phenotyping of 100s of plants, our first objective was to establish near-infrared reflectance spectroscopic (NIRS) predictive equations in order to estimate oil, protein, carbon, and nitrogen content in Arabidopsis seed with high-throughput level. Our results demonstrated that NIRS is a powerful non-destructive, high-throughput method to assess the content of these four major components studied in Arabidopsis seed. With this tool in hand, we analyzed Arabidopsis natural variation for these four components and illustrated that they all displayed a wide range of variation. Finally, NIRS was used in order to map QTL for these four traits using seeds from the Arabidopsis thaliana Ct-1 × Col-0 recombinant inbred line population. Some QTL co-localized with QTL previously identified, but others mapped to chromosomal regions never identified so far for such traits. This paper illustrates the usefulness of NIRS predictive equations to perform accurate high-throughput phenotyping of Arabidopsis seed content, opening new perspectives in gene identification following QTL mapping and genome wide association studies. PMID:27891138

This review describes the use of high-throughput flow cytometry for performing multiplexed cell-based and bead-based screens. With the many advances in cell-based analysis and screening, flow cytometry has historically been underutilized as a screening tool largely due to the limitations in handling large numbers of samples. However, there has been a resurgence in the use of flow cytometry due to a combination of innovations around instrumentation and a growing need for cell-based and bead-based applications. The HTFC™ Screening System (IntelliCyt Corporation, Albuquerque, NM) is a novel flow cytometry-based screening platform that incorporates a fast sample-loading technology, HyperCyt®, with a two-laser, six-parameter flow cytometer and powerful data analysis capabilities. The system is capable of running multiplexed screening assays at speeds of up to 40 wells per minute, enabling the processing of a 96- and 384-well plates in as little as 3 and 12 min, respectively. Embedded in the system is HyperView®, a data analysis software package that allows rapid identification of hits from multiplexed high-throughput flow cytometry screening campaigns. In addition, the software is incorporated into a server-based data management platform that enables seamless data accessibility and collaboration across multiple sites. High-throughput flow cytometry using the HyperCyt technology has been applied to numerous assay areas and screening campaigns, including efflux transporters, whole cell and receptor binding assays, functional G-protein-coupled receptor screening, in vitro toxicology, and antibody screening.

Interest in nano-scale manufacturing research and development is growing. The reason is to accelerate the translation of discoveries and inventions of nanoscience and nanotechnology into products that would benefit industry, economy and society. Ongoing research in nanomanufacturing is focused primarily on developing novel nanofabrication techniques for a variety of applications—materials, energy, electronics, photonics, biomedical, etc. Our goal is to foster the development of high-throughput methods of fabricating nano-enabled products. Large-area parallel processing and highspeed continuous processing are high-throughput means for mass production. An example of large-area processing is step-and-repeat nanoimprinting, by which nanostructures are reproduced again and again over a large area, such as a 12 in wafer. Roll-to-roll processing is an example of continuous processing, by which it is possible to print and imprint multi-level nanostructures and nanodevices on a moving flexible substrate. The big pay-off is high-volume production and low unit cost. However, the anticipated cost benefits can only be realized if the increased production rate is accompanied by high yields of high quality products. To ensure product quality, we need to design and construct manufacturing systems such that the processes can be closely monitored and controlled. One approach is to bring cyber-physical systems (CPS) concepts to nanomanufacturing. CPS involves the control of a physical system such as manufacturing through modeling, computation, communication and control. Such a closely coupled system will involve in-situ metrology and closed-loop control of the physical processes guided by physics-based models and driven by appropriate instrumentation, sensing and actuation. This paper will discuss these ideas in the context of controlling high-throughput manufacturing at the nano-scale.

Each B-cell receptor consists of a pair of heavy and light chains. High-throughput sequencing can identify large numbers of heavy- and light-chain variable regions (V(H) and V(L)) in a given B-cell repertoire, but information about endogenous pairing of heavy and light chains is lost after bulk lysis of B-cell populations. Here we describe a way to retain this pairing information. In our approach, single B cells (>5 × 10(4) capacity per experiment) are deposited in a high-density microwell plate (125 pl/well) and lysed in situ. mRNA is then captured on magnetic beads, reverse transcribed and amplified by emulsion V(H):V(L) linkage PCR. The linked transcripts are analyzed by Illumina high-throughput sequencing. We validated the fidelity of V(H):V(L) pairs identified by this approach and used the method to sequence the repertoire of three human cell subsets-peripheral blood IgG(+) B cells, peripheral plasmablasts isolated after tetanus toxoid immunization and memory B cells isolated after seasonal influenza vaccination.

The advent of human-induced pluripotent stem (hiPS) cell-derived neurons promised to provide better model cells for drug discovery in the context of the central nervous system. This work demonstrates both the upscaling of cellular expansion and the acceleration of neuronal differentiation to accommodate the immense material needs of a high-throughput screening (HTS) approach. Using GRowth factor-driven expansion and INhibition of NotCH (GRINCH) during maturation, the derived cells are here referred to as GRINCH neurons. GRINCH cells displayed neuronal markers, and their functional activity could be demonstrated by electrophysiological recordings. In an application of GRINCH neurons, the brain-derived neurotrophic factor (BDNF)-mediated activation of tropomyosin receptor kinase (TrkB) was investigated as a promising drug target to treat synaptic dysfunctions. To assess the phosphorylation of endogenous TrkB in the GRINCH cells, the highly sensitive amplified luminescent proximity homogeneous assay LISA (AlphaLISA) format was established as a primary screen. A high-throughputreverse transcription (RT)-PCR format was employed as a secondary assay to analyze TrkB-mediated downstream target gene expression. In summary, an optimized differentiation protocol, highly efficient cell upscaling, and advanced assay miniaturization, combined with increased detection sensitivity, pave the way for a new generation of predictive cell-based drug discovery.

A tool to assist in the design of primers for DNA amplification. The Express Primer web-based tool generates primer sequences specifically for the generation of expression clones for both lab scale and high-throughput projects. The application is designed not only to allow the user complete flexibility to specify primer design parameters but also to minimize the amount of manual intervention needed to generate a large number of primers for simultaneous amplification of multiple target genes. The Express Primer Tool enables the user to specify various experimental parameters (e.g. optimal Tm, Tm range, maximum Tm difference) for single or multiple candidate sequence(s) in FASTA format input as a flat text (ASCII) file. The application generates condidate primers, selects optimal primer pairs, and writes the forward and reverse primers pairs to an Excel file that is suitable for electronic submission to a synthesis facility. The program parameters emphasize high-throughput but allow for target atrition at various stages of the project.

High-throughput sequencing is becoming increasingly important in microbial ecology, yet it is surprisingly under-used to generate or test biogeographic hypotheses. In this contribution, we highlight how adding these methods to the ecologist toolbox will allow the detection of new patterns, and will help our understanding of the structure and dynamics of diversity. Starting with a review of ecological questions that can be addressed, we move on to the technical and analytical issues that will benefit from an increased collaboration between different disciplines. PMID:23610649

In the analysis of high-throughput data, a very common goal is the detection of genes or of differential expression between two groups or classes. A recent finding from the scientific literature in prostate cancer demonstrates that by searching for a different pattern of differential expression, new candidate oncogenes might be found. In this chapter, we discuss the statistical problem, termed oncogene outlier detection, and discuss a variety of proposals to this problem. A statistical model in the multiclass situation is described; links with multiple testing concepts are established. Some new nonparametric procedures are described and compared to existing methods using simulation studies.

Highthroughput electrophoresis systems which provide extended well-to-read distances on smaller substrates, thus compacting the overall systems. The electrophoresis systems utilize a high density array of microchannels for electrophoresis analysis with extended read lengths. The microchannel geometry can be used individually or in conjunction to increase the effective length of a separation channel while minimally impacting the packing density of channels. One embodiment uses sinusoidal microchannels, while another embodiment uses plural microchannels interconnected by a via. The extended channel systems can be applied to virtually any type of channel confined chromatography.

The need for adaptive sampling arises in the context of highthroughput data because the rates of data arrival are many orders of magnitude larger than the rates at which they can be analyzed. A very fast decision must therefore be made regarding the value of each incoming observation and its inclusion in the analysis. In this report we discuss one approach to adaptive sampling, based on the new data point’s similarity to the other data points being considered for inclusion. We present preliminary results for one real and one synthetic data set.

Bioconductor is an open-source, open-development software project for the analysis and comprehension of high-throughput data in genomics and molecular biology. The project aims to enable interdisciplinary research, collaboration and rapid development of scientific software. Based on the statistical programming language R, Bioconductor comprises 934 interoperable packages contributed by a large, diverse community of scientists. Packages cover a range of bioinformatic and statistical applications. They undergo formal initial review and continuous automated testing. We present an overview for prospective users and contributors. PMID:25633503

handle job failures due to hardware, software, or network interruptions (obviating the need to manually resubmit the job after each stoppage); be affordable; and most importantly, allow us to complete very large, complex analyses that otherwise would not even be possible. In short, we envisioned a job-management system that would take advantage of unused FORT CPUs within a local area network (LAN) to effectively distribute and run highly complex analytical processes. What we found was a solution that uses HighThroughput Computing (HTC) and High Performance Computing (HPC) systems to do exactly that (Figure 1).

Live cell optical sensing employs label-free optical biosensors to non-invasively measure stimulus-induced dynamic mass redistribution (DMR) in live cells within the sensing volume of the biosensor. The resultant DMR signal is an integrated cellular response, and reflects cell signaling mediated through the cellular target(s) with which the stimulus intervenes. This article describes the uses of live cell optical sensing for probing cell biology and ligand pharmacology, with an emphasis of resonant waveguide grating biosensor cellular assays for highthroughput applications.

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein (Cas) system facilitates targeted genome editing in organisms. Despite high demand of this system, finding a reliable tool for the determination of specific target sites in large genomic data remained challenging. Here, we report SSFinder, a python script to perform highthroughput detection of specific target sites in large nucleotide datasets. The SSFinder is a user-friendly tool, compatible with Windows, Mac OS, and Linux operating systems, and freely available online.

We have developed a high-throughput technology that allows parallel expression, purification, and analysis of large numbers of cloned cDNAs in the yeast Saccharomyces cerevisiae. The technology is based on a vector for intracellular protein expression under control of the inducible CUP1 promoter, where the gene products are fused to specific peptide sequences. These N-terminal and C-terminal epitope tags allow the immunological identification and purification of the gene products independent of the protein produced. By introducing the method of recombinational cloning we avoid time-consuming re-cloning steps and enable the easy switching between different expression vectors and host systems.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

Soluble polymers have emerged as viable alternatives to resin supports across the broad spectrum of high-throughput organic chemistry. As the application of these supports become more widespread, issues such as broad-spectrum solubility and loading are becoming limiting factors and therefore new polymers are required to overcome such limitations. This article details the approach made within our group to new soluble polymer supports and specifically focuses on parallel libraries of block copolymers, de novo poly(styrene-co-chloromethylstyrene), PEG- stealth stars, and substituted poly(norbornylene)s.

High-throughput (HTP) proteomics is a rapidly developing field that offers the global profiling of proteins from a biological system. The HTP technological advances are fueling a revolution in biology, enabling analyses at the scales of entire systems (e.g., whole cells, tumors, or environmental communities). However, simply identifying the proteins in a cell is insufficient for understanding the underlying complexity and operating mechanisms of the overall system. Systems level investigations are relying more and more on computational analyses, especially in the field of proteomics generating large-scale global data.

Recent technical advances in quantitative real-time PCR (qRT-PCR) have allowed for extensive miniaturization, thereby rendering the technique amenable to high-throughput assays. Large numbers of different nucleic acids can now rapidly be measured quantitatively. Many investigations can benefit from this approach, including determination of gene expression in hundreds of samples, determination of hundreds of genes in a few samples, or even quantification of nucleic acids other than mRNA. A simple technique is described here to quantify 1880 transcripts of choice from any number of starting RNA samples.

We review the state of the art and explain the need for better SO2 oxidation catalysts for the production of sulfuric acid. A high-throughput technology has been developed for the study of potential catalysts in the oxidation of SO2 to SO3. High-throughput methods are reviewed and the problems encountered with their adaptation to the corrosive conditions of SO2 oxidation are described. We show that while emissivity-corrected infrared thermography (ecIRT) can be used for primary screening, it is prone to errors because of the large variations in the emissivity of the catalyst surface. UV-visible (UV-Vis) spectrometry was selected instead as a reliable analysis method of monitoring the SO2 conversion. Installing plain sugar absorbents at reactor outlets proved valuable for the detection and quantitative removal of SO3 from the product gas before the UV-Vis analysis. We also overview some elements used for prescreening and those remaining after the screening of the first catalyst generations.

It has been recently known that not only the presence of inhibitory molecules associated with myelin but also the reduced growth capability of the axons limit mature central nervous system (CNS) axonal regeneration after injury. Conventional axon growth studies are typically conducted using multi-well cell culture plates that are very challenging to investigate localized effects of drugs and limited to low throughput. Unfortunately, there is currently no other in vitro tools that allow investigating localized axonal responses to biomolecules in high-throughput for screening potential drugs that might promote axonal growth. We have developed a compartmentalized neuron culture platform enabling localized biomolecular treatments in parallel to axons that are physically and fluidically isolated from their neuronal somata. The 24 axon compartments in the developed platform are designed to perform four sets of six different localized biomolecular treatments simultaneously on a single device. In addition, the novel microfluidic configuration allows culture medium of 24 axon compartments to be replenished altogether by a single aspiration process, making high-throughput drug screening a reality. PMID:27928514

Introduction Flow cytometry has been around for over 40 years, but only recently has the opportunity arisen to move into the high-throughput domain. The technology is now available and is highly competitive with imaging tools under the right conditions. Flow cytometry has, however, been a technology that has focused on its unique ability to study single cells and appropriate analytical tools are readily available to handle this traditional role of the technology. Areas covered Expansion of flow cytometry to a high-throughput (HT) and high-content technology requires both advances in hardware and analytical tools. The historical perspective of flow cytometry operation as well as how the field has changed and what the key changes have been discussed. The authors provide a background and compelling arguments for moving toward HT flow, where there are many innovative opportunities. With alternative approaches now available for flow cytometry, there will be a considerable number of new applications. These opportunities show strong capability for drug screening and functional studies with cells in suspension. Expert opinion There is no doubt that HT flow is a rich technology awaiting acceptance by the pharmaceutical community. It can provide a powerful phenotypic analytical toolset that has the capacity to change many current approaches to HT screening. The previous restrictions on the technology, based on its reduced capacity for sample throughput, are no longer a major issue. Overcoming this barrier has transformed a mature technology into one that can focus on systems biology questions not previously considered possible. PMID:22708834

Articular cartilage enables efficient and near-frictionless load transmission, but suffers from poor inherent healing capacity. As such, cartilage tissue engineering strategies have focused on mimicking both compositional and mechanical properties of native tissue in order to provide effective repair materials for the treatment of damaged or degenerated joint surfaces. However, given the large number design parameters available (e.g. cell sources, scaffold designs, and growth factors), it is difficult to conduct combinatorial experiments of engineered cartilage. This is particularly exacerbated when mechanical properties are a primary outcome, given the long time required for testing of individual samples. Highthroughput screening is utilized widely in the pharmaceutical industry to rapidly and cost-effectively assess the effects of thousands of compounds for therapeutic discovery. Here we adapted this approach to develop a highthroughput mechanical screening (HTMS) system capable of measuring the mechanical properties of up to 48 materials simultaneously. The HTMS device was validated by testing various biomaterials and engineered cartilage constructs and by comparing the HTMS results to those derived from conventional single sample compression tests. Further evaluation showed that the HTMS system was capable of distinguishing and identifying 'hits', or factors that influence the degree of tissue maturation. Future iterations of this device will focus on reducing data variability, increasing force sensitivity and range, as well as scaling-up to even larger (96-well) formats. This HTMS device provides a novel tool for cartilage tissue engineering, freeing experimental design from the limitations of mechanical testing throughput.

First principles methodologies have grown in accuracy and applicability to the point where large databases can be built, shared, and analyzed with the goal of predicting novel compositions, optimizing functional properties, and discovering unexpected relationships between the data. In order to be useful to a large community of users, data should be standardized, validated, and distributed. In addition, tools to easily manage large datasets should be made available to effectively lead to materials development. Within the AFLOW consortium we have developed a simple frame to expand, validate, and mine data repositories: the MTFrame. Our minimalistic approach complement AFLOW and other existing high-throughput infrastructures and aims to integrate data generation with data analysis. We present few examples from our work on materials for energy conversion. Our intent s to pinpoint the usefulness of high-throughput methodologies to guide the discovery process by quantitatively structuring the scientific intuition. This work was supported by ONR-MURI under Contract N00014-13-1-0635 and the Duke University Center for Materials Genomics.

Articular cartilage enables efficient and near-frictionless load transmission, but suffers from poor inherent healing capacity. As such, cartilage tissue engineering strategies have focused on mimicking both compositional and mechanical properties of native tissue in order to provide effective repair materials for the treatment of damaged or degenerated joint surfaces. However, given the large number design parameters available (e.g. cell sources, scaffold designs, and growth factors), it is difficult to conduct combinatorial experiments of engineered cartilage. This is particularly exacerbated when mechanical properties are a primary outcome given the long time required for testing of individual samples. Highthroughput screening is utilized widely in the pharmaceutical industry to rapidly and cost-effectively assess the effects of thousands of compounds for therapeutic discovery. Here we adapted this approach to develop a highthroughput mechanical screening (HTMS) system capable of measuring the mechanical properties of up to 48 materials simultaneously. The HTMS device was validated by testing various biomaterials and engineered cartilage constructs and by comparing the HTMS results to those derived from conventional single sample compression tests. Further evaluation showed that the HTMS system was capable of distinguishing and identifying ‘hits’, or factors that influence the degree of tissue maturation. Future iterations of this device will focus on reducing data variability, increasing force sensitivity and range, as well as scaling-up to even larger (96-well) formats. This HTMS device provides a novel tool for cartilage tissue engineering, freeing experimental design from the limitations of mechanical testing throughput. PMID:24275442

Micro-x-ray fluorescence (MXRF) is a useful characterization tool for high-throughput screening of combinatorial libraries. Due to the increasing threat of use of chemical warfare (CW) agents both in military actions and against civilians by terrorist extremists, there is a strong push to improve existing methods and develop means for the detection of a broad spectrum of CW agents in a minimal amount of time to increase national security. This paper describes a combinatorial high-throughput screening technique for CW receptor discovery to aid in sensor development. MXRF can screen materials for elemental composition at the mesoscale level (tens to hundreds of micrometers). The key aspect of this work is the use of commercial MXRF instrumentation coupled with the inherent heteroatom elements within the target molecules of the combinatorial reaction to provide rapid and specific identification of lead species. The method is demonstrated by screening an 11-mer oligopeptide library for selective binding of the degradation products of the nerve agent VX. The identified oligopeptides can be used as selective molecular receptors for sensor development. The MXRF screening method is nondestructive, requires minimal sample preparation or special tags for analysis, and the screening time depends on the desired sensitivity.

Micro-x-ray fluorescence (MXRF) is a useful characterization tool for high-throughput screening of combinatorial libraries. Due to the increasing threat of use of chemical warfare (CW) agents both in military actions and against civilians by terrorist extremists, there is a strong push to improve existing methods and develop means for the detection of a broad spectrum of CW agents in a minimal amount of time to increase national security. This paper describes a combinatorial high-throughput screening technique for CW receptor discovery to aid in sensor development. MXRF can screen materials for elemental composition at the mesoscale level (tens to hundreds of micrometers). The key aspect of this work is the use of commercial MXRF instrumentation coupled with the inherent heteroatom elements within the target molecules of the combinatorial reaction to provide rapid and specific identification of lead species. The method is demonstrated by screening an 11-mer oligopeptide library for selective binding of the degradation products of the nerve agent VX. The identified oligopeptides can be used as selective molecular receptors for sensor development. The MXRF screening method is nondestructive, requires minimal sample preparation or special tags for analysis, and the screening time depends on the desired sensitivity.

Expression of insoluble protein in E. coli is a major bottleneck of highthroughput structural biology projects. Refolding proteins into native conformations from inclusion bodies could significantly increase the number of protein targets that can be taken on to structural studies. This chapter presents a simple assay for screening insoluble protein targets and identifying those that are most amenable to refolding. The assay is based on the observation that when proteins are refolded while bound to metal affinity resin, misfolded proteins are generally not eluted by imidazole. This difference is exploited here to distinguish between folded and misfolded proteins. Two implementations of the assay are described. The assay fits well into a standard highthroughput structural biology pipeline, because it begins with the inclusion body preparations that are a byproduct of small-scale, automated expression and purification trials and does not require additional facilities. Two formats of the assay are described, a manual assay that is useful for screening small numbers of targets, and an automated implementation that is useful for large numbers of targets.

Tissue microarray (TMA) technology allows rapid visualization of molecular targets in thousands of tissue specimens at a time and provides valuable information on expression of proteins within tissues at a cellular and sub-cellular level. TMA technology overcomes the bottleneck of traditional tissue analysis and allows it to catch up with the rapid advances in lead discovery. Studies using TMA on immunohistochemistry (IHC) can produce a large amount of images for interpretation within a very short time. Manual interpretation does not allow accurate quantitative analysis of staining to be undertaken. Automatic image capture and analysis has been shown to be superior to manual interpretation. The aims of this work is to develop a truly high-throughput and fully automated image capture and analysis system. We develop a robust colour segmentation algorithm using hue-saturation-intensity (HSI) colour space to provide quantification of signal intensity and partitioning of staining on high-throughput TMA. Initial segmentation results and quantification data have been achieved on 16,000 TMA colour images over 23 different tissue types.

We review the state of the art and explain the need for better SO2 oxidation catalysts for the production of sulfuric acid. A high-throughput technology has been developed for the study of potential catalysts in the oxidation of SO2 to SO3. High-throughput methods are reviewed and the problems encountered with their adaptation to the corrosive conditions of SO2 oxidation are described. We show that while emissivity-corrected infrared thermography (ecIRT) can be used for primary screening, it is prone to errors because of the large variations in the emissivity of the catalyst surface. UV-visible (UV-Vis) spectrometry was selected instead as a reliable analysis method of monitoring the SO2 conversion. Installing plain sugar absorbents at reactor outlets proved valuable for the detection and quantitative removal of SO3 from the product gas before the UV-Vis analysis. We also overview some elements used for prescreening and those remaining after the screening of the first catalyst generations. PMID:27877427

Fragment screening, an emerging approach for hit finding in drug discovery, has recently been proven effective by its first approved drug, vemurafenib, for cancer treatment. Techniques such as nuclear magnetic resonance, surface plasmon resonance, and isothemal titration calorimetry, with their own pros and cons, have been employed for screening fragment libraries. As an alternative approach, screening based on high-performance liquid chromatography separation has been developed. In this work, we present weak affinity LC/MS as a method to screen fragments under high-throughput conditions. Affinity-based capillary columns with immobilized thrombin were used to screen a collection of 590 compounds from a fragment library. The collection was divided into 11 mixtures (each containing 35 to 65 fragments) and screened by MS detection. The primary screening was performed in <4 h (corresponding to >3500 fragments per day). Thirty hits were defined, which subsequently entered a secondary screening using an active site-blocked thrombin column for confirmation of specificity. One hit showed selective binding to thrombin with an estimated dissociation constant (K (D)) in the 0.1 mM range. This study shows that affinity LC/MS is characterized by highthroughput, ease of operation, and low consumption of target and fragments, and therefore it promises to be a valuable method for fragment screening.

Highthroughput technologies have the potential to affect all aspects of drug discovery. Considerable attention is paid to highthroughput screening (HTS) for small molecule lead compounds. The identification of the targets that enter those HTS campaigns had been driven by basic research until the advent of genomics level data acquisition such as sequencing and gene expression microarrays. Large-scale profiling approaches (e.g., microarrays, protein analysis by mass spectrometry, and metabolite profiling) can yield vast quantities of data and important information. However, these approaches usually require painstaking in silico analysis and low-throughput basic wet-lab research to identify the function of a gene and validate the gene product as a potential therapeutic drug target. Functional genomic screening offers the promise of direct identification of genes involved in phenotypes of interest. In this review, RNA interference (RNAi) mediated loss-of-function screens will be discussed and as well as their utility in target identification. Some of the genes identified in these screens should produce similar phenotypes if their gene products are antagonized with drugs. With a carefully chosen phenotype, an understanding of the biology of RNAi and appreciation of the limitations of RNAi screening, there is great potential for the discovery of new drug targets.

Highthroughput instruments and analysis techniques are required in order to make good use of the genomic sequences that have recently become available for many species, including humans. These instruments and methods must work with tens of thousands of genes simultaneously, and must be able to identify the small subsets of those genes that are implicated in the observed phenotypes, or, for instance, in responses to therapies. Microarrays represent one such highthroughput method, which continue to find increasingly broad application. This project has improved microarray technology in several important areas. First, we developed the hyperspectral scanner, which has discovered and diagnosed numerous flaws in techniques broadly employed by microarray researchers. Second, we used a series of statistically designed experiments to identify and correct errors in our microarray data to dramatically improve the accuracy, precision, and repeatability of the microarray gene expression data. Third, our research developed new informatics techniques to identify genes with significantly different expression levels. Finally, natural language processing techniques were applied to improve our ability to make use of online literature annotating the important genes. In combination, this research has improved the reliability and precision of laboratory methods and instruments, while also enabling substantially faster analysis and discovery.

Large biological datasets are being produced at a rapid pace and create substantial storage challenges, particularly in the domain of high-throughput sequencing (HTS). Most approaches currently used to store HTS data are either unable to quickly adapt to the requirements of new sequencing or analysis methods (because they do not support schema evolution), or fail to provide state of the art compression of the datasets. We have devised new approaches to store HTS data that support seamless data schema evolution and compress datasets substantially better than existing approaches. Building on these new approaches, we discuss and demonstrate how a multi-tier data organization can dramatically reduce the storage, computational and network burden of collecting, analyzing, and archiving large sequencing datasets. For instance, we show that spliced RNA-Seq alignments can be stored in less than 4% the size of a BAM file with perfect data fidelity. Compared to the previous compression state of the art, these methods reduce dataset size more than 40% when storing exome, gene expression or DNA methylation datasets. The approaches have been integrated in a comprehensive suite of software tools (http://goby.campagnelab.org) that support common analyses for a range of high-throughput sequencing assays. PMID:24260313

Highthroughput macromolecular structure determination is very essential in structural genomics as the available number of sequence information far exceeds the number of available 3D structures. ACORN, a freely available resource in the CCP4 suite of programs is a comprehensive and efficient program for phasing in the determination of protein structures, when atomic resolution data are available. ACORN with the automatic model-building program ARP/wARP and refinement program REFMAC is a suitable combination for the highthroughput structural genomics. ACORN can also be run with secondary structural elements like helices and sheets as inputs with high resolution data. In situations, where ACORN phasing is not sufficient for building the protein model, the fragments (incomplete model/dummy atoms) can again be used as a starting input. Iterative ACORN is proved to work efficiently in the subsequent model building stages in congerin (PDB-ID: lis3) and catalase (PDB-ID: 1gwe) for which models are available.

Recent progress in high-throughput data acquisition has shifted the focus from data generation to processing and understanding of how to integrate collected information. Context specific reconstruction based on generic genome scale models like ReconX or HMR has the potential to become a diagnostic and treatment tool tailored to the analysis of specific individuals. The respective computational algorithms require a high level of predictive power, robustness and sensitivity. Although multiple context specific reconstruction algorithms were published in the last 10 years, only a fraction of them is suitable for model building based on human high-throughput data. Beside other reasons, this might be due to problems arising from the limitation to only one metabolic target function or arbitrary thresholding. This review describes and analyses common validation methods used for testing model building algorithms. Two major methods can be distinguished: consistency testing and comparison based testing. The first is concerned with robustness against noise, e.g., missing data due to the impossibility to distinguish between the signal and the background of non-specific binding of probes in a microarray experiment, and whether distinct sets of input expressed genes corresponding to i.e., different tissues yield distinct models. The latter covers methods comparing sets of functionalities, comparison with existing networks or additional databases. We test those methods on several available algorithms and deduce properties of these algorithms that can be compared with future developments. The set of tests performed, can therefore serve as a benchmarking procedure for future algorithms. PMID:26834640

Single-nucleotide polymorphism (SNP) was one-base variations in DNA sequence that can often be helpful to find genes associations for hereditary disease, communicable disease and so on. We developed a highthroughput SNP detection system based on magnetic nanoparticles (MNPs) separation and dual-color hybridization or single base extension. This system includes a magnetic separation unit for sample separation, three high precision robot arms for pipetting and microtiter plate transferring respectively, an accurate temperature control unit for PCR and DNA hybridization and a high accurate and sensitive optical signal detection unit for fluorescence detection. The cyclooxygenase-2 gene promoter region--65G > C polymorphism locus SNP genotyping experiment for 48 samples from the northern Jiangsu area has been done to verify that if this system can simplify manual operation of the researchers, save time and improve efficiency in SNP genotyping experiments. It can realize sample preparation, target sequence amplification, signal detection and data analysis automatically and can be used in clinical molecule diagnosis and highthroughput fluorescence immunological detection and so on.

High-throughput screens can rapidly scan and capture large amounts of information across multiple biological parameters. Although many screens have been designed to uncover potential new therapeutic targets capable of crippling viruses that cause disease, there have been relatively few directed at improving the efficacy of viruses that are used to treat disease. Oncolytic viruses (OVs) are biotherapeutic agents with an inherent specificity for treating malignant disease. Certain OV platforms – including those based on herpes simplex virus, reovirus, and vaccinia virus – have shown success against solid tumors in advanced clinical trials. Yet, many of these OVs have only undergone minimal engineering to solidify tumor specificity, with few extra modifications to manipulate additional factors. Several aspects of the interaction between an OV and a tumor-bearing host have clear value as targets to improve therapeutic outcomes. At the virus level, these include delivery to the tumor, infectivity, productivity, oncolysis, bystander killing, spread, and persistence. At the host level, these include engaging the immune system and manipulating the tumor microenvironment. Here, we review the chemical- and genome-based high-throughput screens that have been performed to manipulate such parameters during OV infection and analyze their impact on therapeutic efficacy. We further explore emerging themes that represent key areas of focus for future research. PMID:27579293

Motivation: High-throughput ChIP-seq studies typically identify thousands of peaks for a single transcription factor (TF). It is common for traditional motif discovery tools to predict motifs that are statistically significant against a naïve background distribution but are of questionable biological relevance. Results: We describe a simple yet effective algorithm for discovering differential motifs between two sequence datasets that is effective in eliminating systematic biases and scalable to large datasets. Tested on 207 ENCODE ChIP-seq datasets, our method identifies correct motifs in 78% of the datasets with known motifs, demonstrating improvement in both accuracy and efficiency compared with DREME, another state-of-art discriminative motif discovery tool. More interestingly, on the remaining more challenging datasets, we identify common technical or biological factors that compromise the motif search results and use advanced features of our tool to control for these factors. We also present case studies demonstrating the ability of our method to detect single base pair differences in DNA specificity of two similar TFs. Lastly, we demonstrate discovery of key TF motifs involved in tissue specification by examination of high-throughput DNase accessibility data. Availability: The motifRG package is publically available via the bioconductor repository. Contact: yzizhen@fhcrc.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24162561

We report on the development of a vertical and transparent microfluidic chip for high-throughput phenotyping of Arabidopsis thaliana plants. Multiple Arabidopsis seeds can be germinated and grown hydroponically over more than two weeks in the chip, thus enabling large-scale and quantitative monitoring of plant phenotypes. The novel vertical arrangement of this microfluidic device not only allows for normal gravitropic growth of the plants but also, more importantly, makes it convenient to continuously monitor phenotypic changes in plants at the whole organismal level, including seed germination and root and shoot growth (hypocotyls, cotyledons, and leaves), as well as at the cellular level. We also developed a hydrodynamic trapping method to automatically place single seeds into seed holding sites of the device and to avoid potential damage to seeds that might occur during manual loading. We demonstrated general utility of this microfluidic device by showing clear visible phenotypes of the immutans mutant of Arabidopsis, and we also showed changes occurring during plant-pathogen interactions at different developmental stages. Arabidopsis plants grown in the device maintained normal morphological and physiological behaviour, and distinct phenotypic variations consistent with a priori data were observed via high-resolution images taken in real time. Moreover, the timeline for different developmental stages for plants grown in this device was highly comparable to growth using a conventional agar plate method. This prototype plant chip technology is expected to lead to the establishment of a powerful experimental and cost-effective framework for high-throughput and precise plant phenotyping.

Rapidly improving high-throughput sequencing technologies provide unprecedented opportunities for carrying out population-genomic studies with various organisms. To take full advantage of these methods, it is essential to correctly estimate allele and genotype frequencies, and here we present a maximum-likelihood method that accomplishes these tasks. The proposed method fully accounts for uncertainties resulting from sequencing errors and biparental chromosome sampling and yields essentially unbiased estimates with minimal sampling variances with moderately high depths of coverage regardless of a mating system and structure of the population. Moreover, we have developed statistical tests for examining the significance of polymorphisms and their genotypic deviations from Hardy-Weinberg equilibrium. We examine the performance of the proposed method by computer simulations and apply it to low-coverage human data generated by high-throughput sequencing. The results show that the proposed method improves our ability to carry out population-genomic analyses in important ways. The software package of the proposed method is freely available from https://github.com/Takahiro-Maruki/Package-GFE.

Starch is the most important long-term reserve in trees, and the analysis of starch is therefore useful source of physiological information. Currently published protocols for wood starch analysis impose several limitations, such as long procedures and a neutralization step. The high-throughput standard protocols for starch analysis in food and feed represent a valuable alternative. However, they have not been optimised or tested with woody samples. These have particular chemical and structural characteristics, including the presence of interfering secondary metabolites, low reactivity of starch, and low starch content. In this study, a standard method for starch analysis used for food and feed (AOAC standard method 996.11) was optimised to improve precision and accuracy for the analysis of starch in wood. Key modifications were introduced in the digestion conditions and in the glucose assay. The optimised protocol was then evaluated through 430 starch analyses of standards at known starch content, matrix polysaccharides, and wood collected from three organs (roots, twigs, mature wood) of four species (coniferous and flowering plants). The optimised protocol proved to be remarkably precise and accurate (3%), suitable for a highthroughput routine analysis (35 samples a day) of specimens with a starch content between 40 mg and 21 µg. Samples may include lignified organs of coniferous and flowering plants and non-lignified organs, such as leaves, fruits and rhizomes.

Osteoclasts are multinuclear cells that degrade bone under both physiological and pathophysiological conditions. Osteoclasts are therefore a major target of osteoporosis therapeutics aimed at preserving bone. Consequently, analytical methods for osteoclast activity are useful for the development of novel biomarkers and/or pharmacological agents for the treatment of osteoporosis. The nucleation state of an osteoclast is indicative of its maturation and activity. To date, activity is routinely measured at the population level with only approximate consideration of the nucleation state (an 'osteoclast population' is typically defined as cells with ≥3 nuclei). Using a fluorescent substrate for tartrate-resistant acid phosphatase (TRAP), a routinely used marker of osteoclast activity, we developed a multi-labelled imaging method for quantitative measurement of osteoclast TRAP activity at the single cell level. Automated image analysis enables interrogation of large osteoclast populations in a highthroughput manner using open source software. Using this methodology, we investigated the effects of receptor activator of nuclear factor kappa-B ligand (RANK-L) on osteoclast maturation and activity and demonstrated that TRAP activity directly correlates with osteoclast maturity (i.e. nuclei number). This method can be applied to highthroughput screening of osteoclast-targeting compounds to determine changes in maturation and activity.

Microcantilevers are used in a number of applications including atomic-force microscopy (AFM). In this work, deflection-sensing elements along with heating elements are integrated onto micromachined cantilever arrays to increase sensitivity, and reduce complexity and cost. An array of probes with 5–10 nm gold ultrathin film sensors on silicon substrates for highthroughput scanning probe microscopy is developed. The deflection sensitivity is 0.2 ppm/nm. Plots of the change in resistance of the sensing element with displacement are used to calibrate the probes and determine probe contact with the substrate. Topographical scans demonstrate highthroughput and nanometer resolution. The heating elements are calibrated and the thermal coefficient of resistance (TCR) is 655 ppm/K. The melting temperature of a material is measured by locally heating the material with the heating element of the cantilever while monitoring the bending with the deflection sensing element. The melting point value measured with this method is in close agreement with the reported value in literature. PMID:23641125

Hyperspectral imaging (HSI) device users often require both high spectral resolution, on the order of 1 nm, and high light-gathering power. A wide entrance slit assures reasonable étendue but degrades spectral resolution. Spectrometers built using HighThroughput Virtual Slit™ (HTVS) technology optimize both parameters simultaneously. Two remote sensing use cases that require high spectral resolution are discussed. First, detection of atmospheric gases with intrinsically narrow absorption lines, such as hydrocarbon vapors or combustion exhaust gases such as NOx and CO2. Detecting exhaust gas species with high precision has become increasingly important in the light of recent events in the automobile industry. Second, distinguishing reflected daylight from emission spectra in the visible and NIR (VNIR) regions is most easily accomplished using the Fraunhofer absorption lines in solar spectra. While ground reflectance spectral features in the VNIR are generally quite broad, the Fraunhofer lines are narrow and provide a signature of intrinsic vs. extrinsic illumination. The HighThroughput Virtual Slit enables higher spectral resolution than is achievable with conventional spectrometers by manipulating the beam profile in pupil space. By reshaping the instrument pupil with reflective optics, HTVS-equipped instruments create a tall, narrow image profile at the exit focal plane, typically delivering 5X or better the spectral resolution achievable with a conventional design.

Implementation of molecular methods in hop (Humulus lupulus L.) breeding is dependent on the availability of sizeable numbers of polymorphic markers and a comprehensive understanding of genetic variation. However, use of molecular marker technology is limited due to expense, time inefficiency, laborious methodology and dependence on DNA sequence information. Diversity arrays technology (DArT) is a high-throughput cost-effective method for the discovery of large numbers of quality polymorphic markers without reliance on DNA sequence information. This study is the first to utilise DArT for hop genotyping, identifying 730 polymorphic markers from 92 hop accessions. The marker quality was high and similar to the quality of DArT markers previously generated for other species; although percentage polymorphism and polymorphism information content (PIC) were lower than in previous studies deploying other marker systems in hop. Genetic relationships in hop illustrated by DArT in this study coincide with knowledge generated using alternate methods. Several statistical analyses separated the hop accessions into genetically differentiated North American and European groupings, with hybrids between the two groups clearly distinguishable. Levels of genetic diversity were similar in the North American and European groups, but higher in the hybrid group. The markers produced from this time and cost-efficient genotyping tool will be a valuable resource for numerous applications in hop breeding and genetics studies, such as mapping, marker-assisted selection, genetic identity testing, guidance in the maintenance of genetic diversity and the directed breeding of superior cultivars.

A simple steady-state kinetic high-throughput assay was developed for the salicylate synthase MbtI from Mycobacterium tuberculosis, which catalyzes the first committed step of mycobactin biosynthesis. The mycobactins are small-molecule iron chelators produced by M. tuberculosis, and their biosynthesis has been identified as a promising target for the development of new antitubercular agents. The assay was miniaturized to a 384-well plate format and high-throughput screening was performed at the National Screening Laboratory for the Regional Centers of Excellence in Biodefense and Emerging Infectious Diseases (NSRB). Three classes of compounds were identified comprising the benzisothiazolones (class I), diarylsulfones (class II), and benzimidazole-2-thiones (class III). Each of these compound series was further pursued to investigate their biochemical mechanism and structure–activity relationships. Benzimidazole-2-thione 4 emerged as the most promising inhibitor owing to its potent reversible inhibition. PMID:21053346

A simple steady-state kinetic high-throughput assay was developed for the salicylate synthase MbtI from Mycobacterium tuberculosis, which catalyzes the first committed step of mycobactin biosynthesis. The mycobactins are small-molecule iron chelators produced by M. tuberculosis, and their biosynthesis has been identified as a promising target for the development of new antitubercular agents. The assay was miniaturized to a 384-well plate format and high-throughput screening was performed at the National Screening Laboratory for the Regional Centers of Excellence in Biodefense and Emerging Infectious Diseases (NSRB). Three classes of compounds were identified comprising the benzisothiazolones (class I), diarylsulfones (class II), and benzimidazole-2-thiones (class III). Each of these compound series was further pursued to investigate their biochemical mechanism and structure-activity relationships. Benzimidazole-2-thione 4 emerged as the most promising inhibitor owing to its potent reversible inhibition.

Abstract Legally certified sturgeon fisheries require population protection and conservation methods, including DNA tests to identify the source of valuable sturgeon roe. However, the available genetic data are insufficient to distinguish between different sturgeon populations, and are even unable to distinguish between some species. We performed high-throughput single-nucleotide polymorphism (SNP)-genotyping analysis on different populations of Russian (Acipenser gueldenstaedtii), Persian (A. persicus), and Siberian (A. baerii) sturgeon species from the Caspian Sea region (Volga and Ural Rivers), the Azov Sea, and two Siberian rivers. We found that Russian sturgeons from the Volga and Ural Rivers were essentially indistinguishable, but they differed from Russian sturgeons in the Azov Sea, and from Persian and Siberian sturgeons. We identified eight SNPs that were sufficient to distinguish these sturgeon populations with 80% confidence, and allowed the development of markers to distinguish sturgeon species. Finally, on the basis of our SNP data, we propose that the A. baerii-like mitochondrial DNA found in some Russian sturgeons from the Caspian Sea arose via an introgression event during the Pleistocene glaciation. In the present study, the high-throughput genotyping analysis of several sturgeon populations was performed. SNP markers for species identification were defined. The possible explanation of the baerii-like mitotype presence in some Russian sturgeons in the Caspian Sea was suggested. PMID:24567827

The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high-throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA "parts" to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications, including gene replacement and the creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.

Background With the continued proliferation of high-throughput biological experiments, there is a pressing need for tools to integrate the data produced in ways that produce biologically meaningful conclusions. Many microarray studies have analysed transcriptomic data from a pathway perspective, for instance by testing for KEGG pathway enrichment in sets of upregulated genes. However, the increasing availability of species-specific metabolic models provides the opportunity to analyse these data in a more objective, system-wide manner. Results Here we introduce ambient (Active Modules for Bipartite Networks), a simulated annealing approach to the discovery of metabolic subnetworks (modules) that are significantly affected by a given genetic or environmental change. The metabolic modules returned by ambient are connected parts of the bipartite network that change coherently between conditions, providing a more detailed view of metabolic changes than standard approaches based on pathway enrichment. Conclusions ambient is an effective and flexible tool for the analysis of high-throughput data in a metabolic context. The same approach can be applied to any system in which reactions (or metabolites) can be assigned a score based on some biological observation, without the limitation of predefined pathways. A Python implementation of ambient is available at http://www.theosysbio.bio.ic.ac.uk/ambient. PMID:23531303

Legally certified sturgeon fisheries require population protection and conservation methods, including DNA tests to identify the source of valuable sturgeon roe. However, the available genetic data are insufficient to distinguish between different sturgeon populations, and are even unable to distinguish between some species. We performed high-throughput single-nucleotide polymorphism (SNP)-genotyping analysis on different populations of Russian (Acipenser gueldenstaedtii), Persian (A. persicus), and Siberian (A. baerii) sturgeon species from the Caspian Sea region (Volga and Ural Rivers), the Azov Sea, and two Siberian rivers. We found that Russian sturgeons from the Volga and Ural Rivers were essentially indistinguishable, but they differed from Russian sturgeons in the Azov Sea, and from Persian and Siberian sturgeons. We identified eight SNPs that were sufficient to distinguish these sturgeon populations with 80% confidence, and allowed the development of markers to distinguish sturgeon species. Finally, on the basis of our SNP data, we propose that the A. baerii-like mitochondrial DNA found in some Russian sturgeons from the Caspian Sea arose via an introgression event during the Pleistocene glaciation. In the present study, the high-throughput genotyping analysis of several sturgeon populations was performed. SNP markers for species identification were defined. The possible explanation of the baerii-like mitotype presence in some Russian sturgeons in the Caspian Sea was suggested.

Changes in cellular mechanical properties correlate with the progression of metastatic cancer along the epithelial-to-mesenchymal transition (EMT). Few high-throughput methodologies exist that measure cell compliance, which can be used to understand the impact of genetic alterations or to screen the efficacy of chemotherapeutic agents. We have developed a novel array high-throughput microscope (AHTM) system that combines the convenience of the standard 96-well plate with the ability to image cultured cells and membrane-bound microbeads in twelve independently-focusing channels simultaneously, visiting all wells in eight steps. We use the AHTM and passive bead rheology techniques to determine the relative compliance of human pancreatic ductal epithelial (HPDE) cells, h-TERT transformed HPDE cells (HPNE), and four gain-of-function constructs related to EMT. The AHTM found HPNE, H-ras, Myr-AKT, and Bcl2 transfected cells more compliant relative to controls, consistent with parallel tests using atomic force microscopy and invasion assays, proving the AHTM capable of screening for changes in mechanical phenotype. PMID:27265611

Recent progress of genetic studies has dramatically unveiled pathogenesis of acute myeloid leukemia (AML). However, overall survival of AML still remains unsatisfactory and development of novel therapeutics is required. CCAAT/Enhancer Binding Protein α (C/EBPα) is one of crucial transcription factors that induce granulocytic differentiation and its activity is perturbed in human myeloid leukemias. As its re-expression can induce differentiation and subsequent apoptosis of leukemic cells in vitro, we hypothesized that chemical compounds that restore C/EBPα expression and/or activity would lead to myeloid differentiation of leukemic cells. Using a cell-based high-throughput screening, we identified 2-[(E)-2-(3,4-dihydroxyphenyl)vinyl]-3-(2-methoxyphenyl)-4(3H)-quinazolinone as a potent inducer of C/EBPα and myeloid differentiation. Leukemia cell lines and primary blast cells isolated from human AML patients treated with ICCB280 demonstrated evidence of morphological and functional differentiation, as well as massive apoptosis. We performed conformational analyses of the high-throughput screening hit compounds to postulate the spatial requirements for high potency. Our results warrant a development of novel differentiation therapies and significantly impact care of AML patients with unfavorable prognosis in the near future. PMID:26109609

Genomic sequencing has implicated large numbers of genes and de novo mutations as potential disease risk factors. A highthroughput in vivo model system is needed to validate gene associations with pathology. We developed a Drosophila-based functional system to screen candidate disease genes identified from Congenital Heart Disease (CHD) patients. 134 genes were tested in the Drosophila heart using RNAi-based gene silencing. Quantitative analyses of multiple cardiac phenotypes demonstrated essential structural, functional, and developmental roles for more than 70 genes, including a subgroup encoding histone H3K4 modifying proteins. We also demonstrated the use of Drosophila to evaluate cardiac phenotypes resulting from specific, patient-derived alleles of candidate disease genes. We describe the first highthroughput in vivo validation system to screen candidate disease genes identified from patients. This approach has the potential to facilitate development of precision medicine approaches for CHD and other diseases associated with genetic factors. DOI: http://dx.doi.org/10.7554/eLife.22617.001 PMID:28084990

Purpose. High-throughput techniques are needed to identify and optimize novel photodynamic therapy (PDT) agents with greater efficacy and to lower toxicity. Novel agents with the capacity to completely ablate pathologic angiogenesis could be of substantial utility in diseases such as wet age-related macular degeneration (AMD). Methods. An instrument and approach was developed based on light-emitting diode (LED) technology for high-throughput screening (HTS) of libraries of potential chemical and biological photosensitizing agents. Ninety-six-well LED arrays were generated at multiple wavelengths and under rigorous intensity control. Cell toxicity was measured in 96-well culture arrays with the nuclear dye SYTOX Green (Invitrogen-Molecular Probes, Eugene, OR). Results. Rapid screening of photoactivatable chemicals or biological molecules has been realized in 96-well arrays of cultured human cells. This instrument can be used to identify new PDT agents that exert cell toxicity on presentation of light of the appropriate energy. The system is further demonstrated through determination of the dose dependence of model compounds having or lacking cellular phototoxicity. Killer Red (KR), a genetically encoded red fluorescent protein expressed from transfected plasmids, is examined as a potential cellular photosensitizing agent and offers unique opportunities as a cell-type–specific phototoxic protein. Conclusions. This instrument has the capacity to screen large chemical or biological libraries for rapid identification and optimization of potential novel phototoxic lead candidates. KR and its derivatives have unique potential in ocular gene therapy for pathologic angiogenesis or tumors. PMID:19834043

It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive, reproducible, and robust to detect potential biomarkers below the level of highly expressed proteins, generate data sets that are comparable between experiments and laboratories, and have highthroughput to support statistical studies. Here we report a method for highthroughput quantitative analysis of serum proteins. It consists of the selective isolation of peptides that are N-linked glycosylated in the intact protein, the analysis of these now deglycosylated peptides by liquid chromatography electrospray ionization mass spectrometry, and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. We provide data that document the performance of the method and show that sera from untreated normal mice and genetically identical mice with carcinogen-induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide patterns. We further identify, by tandem mass spectrometry, some of the peptides that were consistently elevated in cancer mice compared with their control littermates.

Highthroughput (HT) phenotyping of crops is essential to increase yield in environments deteriorated by climate change. The controlled environment of a greenhouse offers an ideal platform to study the genotype to phenotype linkages for crop screening. Advanced imaging technologies are used to study plants' responses to resource limitations such as water and nutrient deficiency. Advanced imaging technologies coupled with automation make HT phenotyping in the greenhouse not only feasible, but practical. Monsanto has a state of the art automated greenhouse (AGH) facility. Handling of the soil, pots water and nutrients are all completely automated. Images of the plants are acquired by multiple hyperspectral and broadband cameras. The hyperspectral cameras cover wavelengths from visible light through short wave infra-red (SWIR). Inhouse developed software analyzes the images to measure plant morphological and biochemical properties. We measure phenotypic metrics like plant area, height, and width as well as biomass. Hyperspectral imaging allows us to measure biochemcical metrics such as chlorophyll, anthocyanin, and foliar water content. The last 4 years of AGH operations on crops like corn, soybean, and cotton have demonstrated successful application of imaging and analysis technologies for highthroughput plant phenotyping. Using HT phenotyping, scientists have been showing strong correlations to environmental conditions, such as water and nutrient deficits, as well as the ability to tease apart distinct differences in the genetic backgrounds of crops.

Changes in cellular mechanical properties correlate with the progression of metastatic cancer along the epithelial-to-mesenchymal transition (EMT). Few high-throughput methodologies exist that measure cell compliance, which can be used to understand the impact of genetic alterations or to screen the efficacy of chemotherapeutic agents. We have developed a novel array high-throughput microscope (AHTM) system that combines the convenience of the standard 96-well plate with the ability to image cultured cells and membrane-bound microbeads in twelve independently-focusing channels simultaneously, visiting all wells in eight steps. We use the AHTM and passive bead rheology techniques to determine the relative compliance of human pancreatic ductal epithelial (HPDE) cells, h-TERT transformed HPDE cells (HPNE), and four gain-of-function constructs related to EMT. The AHTM found HPNE, H-ras, Myr-AKT, and Bcl2 transfected cells more compliant relative to controls, consistent with parallel tests using atomic force microscopy and invasion assays, proving the AHTM capable of screening for changes in mechanical phenotype.

Recent progress in generating a vast number of drug targets through genomics and large compound libraries through combinatorial chemistry have stimulated advancements in drug discovery through the development of new highthroughput screening (HTS) methods. Automation and HTS techniques are also highly desired in fields such as clinical diagnostics. Luminescence-based assays have emerged as an alternative to radiolabel-based assays in HTS as they approach the sensitivity of radioactive detection along with ease of operation, which makes them amenable to miniaturization. Luminescent proteins provide the advantage of reduced reagent and operating costs because they can be produced in unlimited amounts through the use of genetic engineering tools. In that regard, the use of two naturally occurring and recombinantly produced luminescent proteins from the jellyfish Aequorea victoria, namely, aequorin and the green fluorescent protein (GFP), has attracted attention in a number of analytical applications in diverse research areas. Aequorin is naturally bioluminescent and has therefore, virtually no associated background signal, which allows its detection down to attomole levels. GFP has become the reporter of choice in a variety of applications given that it is an autofluorescent protein that does not require addition of any co-factors for fluorescence emission. Furthermore, the generation of various mutants of GFP with differing luminescent and spectral properties has spurred additional interest in this protein. In this review, we focus on the use of aequorin and GFP in the development of highly sensitive assays that find applications in drug discovery and in highthroughput analysis.

Crude extract based cell-free protein synthesis (CFPS) has emerged as a powerful technology platform for high-throughput protein production and genetic part characterization. Unfortunately, robust preparation of highly active extracts generally requires specialized and costly equipment and can be labor and time intensive. Moreover, cell lysis procedures can be hard to standardize, leading to different extract performance across laboratories. These challenges limit new entrants to the field and new applications, such as comprehensive genome engineering programs to improve extract performance. To address these challenges, we developed a generalizable and easily accessible high-throughput crude extract preparation method for CFPS based on sonication. To validate our approach, we investigated two Escherichia coli strains: BL21 Star™ (DE3) and a K12 MG1655 variant, achieving similar productivity (defined as CFPS yield in g/L) by varying only a few parameters. In addition, we observed identical productivity of cell extracts generated from culture volumes spanning three orders of magnitude (10 mL culture tubes to 10 L fermentation). We anticipate that our rapid and robust extract preparation method will speed-up screening of genomically engineered strains for CFPS applications, make possible highly active extracts from non-model organisms, and promote a more general use of CFPS in synthetic biology and biotechnology. PMID:25727242

The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high- throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA “parts” to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications including gene replacement and creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.

Background Identification of historic pathogens is challenging since false positives and negatives are a serious risk. Environmental non-pathogenic contaminants are ubiquitous. Furthermore, public genetic databases contain limited information regarding these species. High-throughput sequencing may help reliably detect and identify historic pathogens. Results We shotgun-sequenced 8 16th-century Mixtec individuals from the site of Teposcolula Yucundaa (Oaxaca, Mexico) who are reported to have died from the huey cocoliztli (‘Great Pestilence’ in Nahautl), an unknown disease that decimated native Mexican populations during the Spanish colonial period, in order to identify the pathogen. Comparison of these sequences with those deriving from the surrounding soil and from 4 precontact individuals from the site found a wide variety of contaminant organisms that confounded analyses. Without the comparative sequence data from the precontact individuals and soil, false positives for Yersinia pestis and rickettsiosis could have been reported. Conclusions False positives and negatives remain problematic in ancient DNA analyses despite the application of high-throughput sequencing. Our results suggest that several studies claiming the discovery of ancient pathogens may need further verification. Additionally, true single molecule sequencing’s short read lengths, inability to sequence through DNA lesions, and limited ancient-DNA-specific technical development hinder its application to palaeopathology. PMID:24568097

As a microorganism of major biotechnological importance, the oleaginous yeast Yarrowia lipolytica is subjected to intensive genetic engineering and functional genomic analysis. Future advancements in this area, however, require a system that will generate a large collection of mutants for high-throughput screening. Here, we report a rapid and efficient method for high-throughput transformation of Y. lipolytica in 96-well plates. We developed plasmids and strains for the large-scale screening of overexpression mutant strains, using Gateway® vectors that were adapted for specific locus integration in Y. lipolytica. As an example, a collection of mutants that overexpressed the alkaline extracellular protease (AEP) was obtained in a single transformation experiment. The platform strain that we developed to receive the overexpression cassette was designed to constitutively express a fluorescent protein as a convenient growth reporter for screening in non-translucid media. An example of growth comparison in skim milk-based medium between AEP overexpression and deletion mutants is provided.

Deubiquitinating enzymes (DUBs) reverse the process of ubiquitination, and number nearly 100 in humans. In principle, DUBs represent promising drug targets, as several of the enzymes have been implicated in human diseases. The isopeptidase activity of DUBs can be selectively inhibited by targeting the catalytic site with drug-like compounds. Notably, the mammalian 26S proteasome is associated with three major DUBs: RPN11, UCH37 and USP14. Because the ubiquitin ‘chain-trimming’ activity of USP14 can inhibit proteasome function, inhibitors of USP14 can stimulate proteasomal degradation. We recently established a high-throughput screening (HTS) method to discover small-molecule inhibitors specific for USP14. The protocols in this article cover the necessary procedures for preparing assay reagents, performing HTS for USP14 inhibitors, and carrying out post-HTS analysis. PMID:23788557

Native mass spectrometry (MS) has become a sensitive method for structural proteomics, allowing practitioners to gain insight into protein self-assembly, including stoichiometry and three-dimensional architecture, as well as complementary thermodynamic and kinetic aspects. Although MS is typically performed in vacuum, a body of literature has described how native solution-state structure is largely retained on the timescale of the experiment. Native MS offers the benefit that it requires substantially smaller quantities of a sample than traditional structural techniques such as NMR and X-ray crystallography, and is therefore well suited to high-throughput studies. Here we first describe the native MS approach and outline the structural proteomic data that it can deliver. We then provide practical details of experiments to examine the structural and dynamic properties of protein assemblies, highlighting potential pitfalls as well as principles of best practice.

The scale, velocity, and dynamic nature of large scale social media systems like Twitter demand a new set of visual analytics techniques that support near real-time situational awareness. Social media systems are credited with escalating social protest during recent large scale riots. Virtual communities form rapidly in these online systems, and they occasionally foster violence and unrest which is conveyed in the users language. Techniques for analyzing broad trends over these networks or reconstructing conversations within small groups have been demonstrated in recent years, but state-of- the-art tools are inadequate at supporting near real-time analysis of these highthroughput streams of unstructured information. In this paper, we present an adaptive system to discover and interactively explore these virtual networks, as well as detect sentiment, highlight change, and discover spatio- temporal patterns.

Summary The constitutive androstane receptor (CAR, NR1I3) is responsible for the transcription of multiple drug metabolizing enzymes and transporters. There are two possible methods of activation for CAR, direct ligand binding and a ligand-independent method, which makes this a unique nuclear receptor. Both of these mechanisms require translocation of CAR from the cytoplasm into the nucleus. Interestingly, CAR is constitutively active in immortalized cell lines due to the basal nuclear location of this receptor. This creates an important challenge in most in vitro assay models because immortalized cells cannot be used without inhibiting the basal activity. In this book chapter, we go into detail of how to perform quantitative high-throughput screens to identify hCAR1 modulators through the employment of a double stable cell line. Using this line, we are able to identify activators, as well as deactivators, of the challenging nuclear receptor, CAR. PMID:27518621

The current state of screening methods for drug discovery is still riddled with several inefficiencies. Although some widely used high-throughput screening platforms may enhance the drug screening process, their cost and oversimplification of cell-drug interactions pose a translational difficulty. Microfluidic cell-chips resolve many issues found in conventional HTS technology, providing benefits such as reduced sample quantity and integration of 3D cell culture physically more representative of the physiological/pathological microenvironment. In this review, we introduce the advantages of microfluidic devices in drug screening, and outline the critical factors which influence device design, highlighting recent innovations and advances in the field including a summary of commercialization efforts on microfluidic cell chips. Future perspectives of microfluidic cell devices are also provided based on considerations of present technological limitations and translational barriers.

Haemostasis occurs at sites of vascular injury, where flowing blood forms a clot, a dynamic and heterogeneous fibrin-based biomaterial. Paramount in the clot's capability to stem haemorrhage are its changing mechanical properties, the major drivers of which are the contractile forces exerted by platelets against the fibrin scaffold. However, how platelets transduce microenvironmental cues to mediate contraction and alter clot mechanics is unknown. This is clinically relevant, as overly softened and stiffened clots are associated with bleeding and thrombotic disorders. Here, we report a high-throughput hydrogel-based platelet-contraction cytometer that quantifies single-platelet contraction forces in different clot microenvironments. We also show that platelets, via the Rho/ROCK pathway, synergistically couple mechanical and biochemical inputs to mediate contraction. Moreover, highly contractile platelet subpopulations present in healthy controls are conspicuously absent in a subset of patients with undiagnosed bleeding disorders, and therefore may function as a clinical diagnostic biophysical biomarker.

To function as flotation collectors for mineral processing, polymeric nanoparticles require a delicate balance of surface properties to give mineral-specific deposition and colloidal stability in high ionic strength alkaline media, while remaining sufficiently hydrophobic to promote flotation. Combinatorial nanoparticle surface modification, in conjunction with highthroughput screening, is a promising approach for nanoparticle development. However, efficient automated screening assays are required to reject ineffective particles without having to undergo time consuming flotation testing. Herein we demonstrate that determining critical coagulation concentrations of sodium carbonate in combination with measuring the advancing water contact angle of nanoparticle-saturated glass surfaces can be used to screen ineffective nanoparticles. Finally, none of our first nanoparticle library based on poly(ethylene glycol) methyl ether methacrylate (PEG-methacrylate) were effective flotation collectors because the nanoparticles were too hydrophilic.

A library of 32 polystyrene copolymer latexes, with diameters ranging between 53 and 387 nm, was used to develop and demonstrate a high-throughput assay using a 96-well microplate platform to measure critical coagulation concentrations, a measure of colloidal stability. The most robust assay involved an automated centrifugation-decantation step to remove latex aggregates before absorbance measurements, eliminating aggregate interference with optical measurements made through the base of the multiwell plates. For smaller nanoparticles (diameter <150 nm), the centrifugation-decantation step was not required as the interference was less than with larger particles. Parallel measurements with a ChemiDoc MP plate scanner gave indications of aggregation; however, the results were less sensitive than the absorbance measurements.

A novel fabrication scheme to develop high-throughput plastic microlenses using injection-molding techniques is realized. The initial microlens mold is fabricated using the well-known reflow technique. The reflow process is optimized to obtain reliable and repeatable microlens patterns. The master mold insert for the injection-molding process is fabricated using metal electroforming. The electroplating process is optimized for obtaining a low stress electroform. Two new plastic materials, cyclo olefin copolymer (COC) and Poly IR 2 are introduced in this work for fabricating microlenses. The plastic microlenses have been characterized for their focal lengths that range from 200 µm to 1.9 mm. This technique enables high-volume production of plastic microlenses with cycle times for a single chip being of the order of 60 s.

The vast range of in silico resources that are available in life sciences research hold much promise towards aiding the drug discovery process. To fully realize this opportunity, computational scientists must consider the practical issues of data integration and identify how best to apply these resources scientifically. In this article we describe in silico approaches that are driven towards the identification of testable laboratory hypotheses; we also address common challenges in the field. We focus on flexible, high-throughput techniques, which may be initiated independently of 'wet-lab' experimentation, and which may be applied to multiple disease areas. The utility of these approaches in drug discovery highlights the contribution that in silico techniques can make and emphasizes the need for collaboration between the areas of disease research and computational science.

Several x-ray astronomy missions of the 1990s will contain focusing telescopes with significantly more collecting power than the Einstein Observatory. There is increasing emphasis on spectroscopy. ESA's XMM with 10(4) cm(2) of effective area will be the largest. A highthroughput facility with over 10(5) cm(2) of effective area and 20-sec of arc angular resolution is needed ultimately for various scientific studies such as high resolution spectroscopic observations of QSOs. At least one of the following techniques currently being developed for fabricating x-ray telescopes including automated figuring of flats as parabolic reflectors, replication of cylindrical shells, and the alignment of thin lacquer-coated conical foils is likely to permit the construction of modular arrays of telescopes with the area and angular resolution required.

Advances in automated and high-throughput imaging technologies have resulted in a deluge of high-resolution images and sensor data of plants. However, extracting patterns and features from this large corpus of data requires the use of machine learning (ML) tools to enable data assimilation and feature identification for stress phenotyping. Four stages of the decision cycle in plant stress phenotyping and plant breeding activities where different ML approaches can be deployed are (i) identification, (ii) classification, (iii) quantification, and (iv) prediction (ICQP). We provide here a comprehensive overview and user-friendly taxonomy of ML tools to enable the plant community to correctly and easily apply the appropriate ML tools and best-practice guidelines for various biotic and abiotic stress traits.

Changes in gene expression are known to contribute to muscle plasticity. Until recently most studies have described differences of one or few genes at a time, in the last few years, however, the development of new technology of highthroughput mRNA expression analysis has allowed the study of a large part if not all transcripts in the same experiment. Knowledge on any muscle adaptive response has already gained from the application of this novel approach, but the most important new findings have come from studies on muscle atrophy. A new and unexpected groups of genes, which increase their expression during atrophy and are, therefore, designated as atrogins, have been discovered. In spite of the impressive power of the new technology many problems are still to be resolved to optimize the experimental design and to extract all information which are provided by the outcome of the global mRNA assessment.

High-throughput data collection requires the seamless interoperation of various hardware components. User-supplied descriptions of protein crystals must also be directly linked with the diffraction data. Such linkages can be achieved efficiently with computer databases. A database that tracks production of the protein samples, crystallization, and diffraction from the resultant crystals serves as the glue that holds the entire gene-to-structure process together. This chapter begins by discussing data collection processes and hardware. It then illustrates how a well-constructed database ensures information flow through the steps of data acquisition. Such a database allows synchrotron beamline measurements to be directly and efficiently integrated into the process of protein crystallographic structure determination.

We have developed a robust and rapid computational method for processing the raw spectral data collected from thin film optical interference biosensors. We have applied this method to Interference Reflectance Imaging Sensor (IRIS) measurements and observed a 10,000 fold improvement in processing time, unlocking a variety of clinical and scientific applications. Interference biosensors have advantages over similar technologies in certain applications, for example highly multiplexed measurements of molecular kinetics. However, processing raw IRIS data into useful measurements has been prohibitively time consuming for high-throughput studies. Here we describe the implementation of a lookup table (LUT) technique that provides accurate results in far less time than naive methods. We also discuss an additional benefit that the LUT method can be used with a wider range of interference layer thickness and experimental configurations that are incompatible with methods that require fitting the spectral response.

Developmental biology has traditionally relied on qualitative analyses; recently, however, as in other fields of biology, researchers have become increasingly interested in acquiring quantitative knowledge about embryogenesis. Advances in fluorescence microscopy are enabling high-content imaging in live specimens. At the same time, microfluidics and automation technologies are increasing experimental throughput for studies of multicellular models of development. Furthermore, computer vision methods for processing and analyzing bioimage data are now leading the way toward quantitative biology. Here, we review advances in the areas of fluorescence microscopy, microfluidics, and data analysis that are instrumental to performing high-content, high-throughput studies in biology and specifically in development. We discuss a case study of how these techniques have allowed quantitative analysis and modeling of pattern formation in the Drosophila embryo.

A microgradient-heater (MGH) was developed, and its feasibility as a tool for high-throughput materials science experimentation was tested. The MGH is derived from microhot plate (MHP) systems and allows combinatorial thermal processing on the micronano scale. The temperature gradient is adjustable by the substrate material. For an Au-coated MGH membrane a temperature drop from 605 to 100 °C was measured over a distance of 965 μm, resulting in an average temperature change of 0.52 K/μm. As a proof of principle, we demonstrate the feasibility of MGHs on the example of a chemical vapor deposition (CVD) process. The achieved results show discontinuous changes in surface morphology within a continuous TiO2 film. Furthermore the MGH can be used to get insights into the energetic relations of film growth processes, giving it the potential for microcalorimetry measurements.

Bulk metallic glasses (BMGs) are materials which may combine key properties from crystalline metals, such as high hardness, with others typically presented by plastics, such as easy processability. However, the cost of the known BMGs poses a significant obstacle for the development of applications, which has lead to a long search for novel, economically viable, BMGs. The emergence of high-throughput DFT calculations, such as the library provided by the AFLOWLIB consortium, has provided new tools for materials discovery. We have used this data to develop a new glass forming descriptor combining structural factors with thermodynamics in order to quickly screen through a large number of alloy systems in the AFLOWLIB database, identifying the most promising systems and the optimal compositions for glass formation. National Science Foundation (DMR-1436151, DMR-1435820, DMR-1436268).

Sequencing methods have improved rapidly since the first versions of the Sanger techniques, facilitating the development of very powerful tools for detecting and identifying various pathogens, such as viruses, bacteria and other microbes. The ongoing development of high-throughput sequencing (HTS; also known as next-generation sequencing) technologies has resulted in a dramatic reduction in DNA sequencing costs, making the technology more accessible to the average laboratory. In this White Paper of the World Organisation for Animal Health (OIE) Collaborating Centre for the Biotechnology-based Diagnosis of Infectious Diseases in Veterinary Medicine (Uppsala, Sweden), several approaches and examples of HTS are summarised, and their diagnostic applicability is briefly discussed. Selected future aspects of HTS are outlined, including the need for bioinformatic resources, with a focus on improving the diagnosis and control of infectious diseases in veterinary medicine.

One of today's key challenges is the ability to decode the functions of complex carbohydrates in various biological contexts. To generate high-quality glycomics data in a high-throughput fashion, we developed a robotized and low-cost N-glycan analysis platform for glycoprofiling of immunoglobulin G antibodies (IgG), which are central players of the immune system and of vital importance in the biopharmaceutical industry. The key features include (a) rapid IgG affinity purification and sample concentration, (b) protein denaturation and glycan release on a multiwell filtration device, (c) glycan purification on solid-supported hydrazide, and (d) glycan quantification by ultra performance liquid chromatography. The sample preparation workflow was automated using a robotic liquid-handling workstation, allowing the preparation of 96 samples (or multiples thereof) in 22 h with excellent reproducibility and, thus, should greatly facilitate biomarker discovery and glycosylation monitoring of therapeutic IgGs.

We demonstrate automated generation of diffusion databases from high-throughput density functional theory (DFT) calculations. A total of more than 230 dilute solute diffusion systems in Mg, Al, Cu, Ni, Pd, and Pt host lattices have been determined using multi-frequency diffusion models. We apply a correction method for solute diffusion in alloys using experimental and simulated values of host self-diffusivity. We find good agreement with experimental solute diffusion data, obtaining a weighted activation barrier RMS error of 0.176 eV when excluding magnetic solutes in non-magnetic alloys. The compiled database is the largest collection of consistently calculated ab-initio solute diffusion data in the world.

The success of combinatorial and high-throughput methodologies relies greatly on the availability of various characterization tools with new and improved capabilities [1]. Indeed, how useful can a combinatorial library of 250, 400, 25 000 or 2 000 000 compounds be [2-5] if one is unable to characterize its properties of interest fairly quickly? How useful can a set of thousands of spectra or chromatograms be if one is unable to analyse them in a timely manner? For these reasons, the development of new approaches for materials characterization is one of the most active areas in combinatorial materials science. The importance of this aspect of research in the field has been discussed in numerous conferences including the Pittsburgh Conferences, the American Chemical Society Meetings, the American Physical Society Meetings, the Materials Research Society Symposia and various Gordon Research Conferences. Naturally, the development of new measurement instrumentation attracts the attention not only of practitioners of combinatorial materials science but also of those who design new software for data manipulation and mining. Experimental designs of combinatorial libraries are pursued with available and realistic synthetic and characterization capabilities in mind. It is becoming increasingly critical to link the design of new equipment for high-throughput parallel materials synthesis with integrated measurement tools in order to enhance the efficacy of the overall experimental strategy. We have received an overwhelming response to our proposal and call for papers for this Special Issue on Combinatorial Materials Science. The papers in this issue of Measurement Science and Technology are a very timely collection that captures the state of modern combinatorial materials science. They demonstrate the significant advances that are taking place in the field. In some cases, characterization tools are now being operated in the factory mode. At the same time, major challenges

Bacterial cells are highly organized with many protein complexes and DNA loci dynamically positioned to distinct subcellular sites over the course of a cell cycle. Such dynamic protein localization is essential for polar organelle development, establishment of asymmetry, and chromosome replication during the Caulobacter crescentus cell cycle. We used a fluorescence microscopy screen optimized for high-throughput to find strains with anomalous temporal or spatial protein localization patterns in transposon-generated mutant libraries. Automated image acquisition and analysis allowed us to identify genes that affect the localization of two polar cell cycle histidine kinases, PleC and DivJ, and the pole-specific pili protein CpaE, each tagged with a different fluorescent marker in a single strain. Four metrics characterizing the observed localization patterns of each of the three labeled proteins were extracted for hundreds of cell images from each of 854 mapped mutant strains. Using cluster analysis of the resulting set of 12-element vectors for each of these strains, we identified 52 strains with mutations that affected the localization pattern of the three tagged proteins. This information, combined with quantitative localization data from epitasis experiments, also identified all previously known proteins affecting such localization. These studies provide insights into factors affecting the PleC/DivJ localization network and into regulatory links between the localization of the pili assembly protein CpaE and the kinase localization pathway. Our high-throughput screening methodology can be adapted readily to any sequenced bacterial species, opening the potential for databases of localization regulatory networks across species, and investigation of localization network phylogenies.

Monoclonal antibodies (mAbs) have become the fastest growing segment in the drug market with annual sales of more than 40 billion US$ in 2013. The selection of lead candidate molecules involves the generation of large repertoires of antibodies from which to choose a final therapeutic candidate. Improvements in the ability to rapidly produce and purify many antibodies in sufficient quantities reduces the lead time for selection which ultimately impacts on the speed with which an antibody may transition through the research stage and into product development. Miniaturization and automation of chromatography using micro columns (RoboColumns(®) from Atoll GmbH) coupled to an automated liquid handling instrument (ALH; Freedom EVO(®) from Tecan) has been a successful approach to establish highthroughput process development platforms. Recent advances in transient gene expression (TGE) using the high-titre Expi293F™ system have enabled recombinant mAb titres of greater than 500mg/L. These relatively high protein titres reduce the volume required to generate several milligrams of individual antibodies for initial biochemical and biological downstream assays, making TGE in the Expi293F™ system ideally suited to highthroughput chromatography on an ALH. The present publication describes a novel platform for purifying Expi293F™-expressed recombinant mAbs directly from cell-free culture supernatant on a Perkin Elmer JANUS-VariSpan ALH equipped with a plate shuttle device. The purification platform allows automated 2-step purification (Protein A-desalting/size exclusion chromatography) of several hundred mAbs per week. The new robotic method can purify mAbs with high recovery (>90%) at sub-milligram level with yields of up to 2mg from 4mL of cell-free culture supernatant.

Human neuronal cells differentiated from induced pluripotent cells have emerged as a new model system for the study of disease pathophysiology and evaluation of drug efficacy. Differentiated neuronal cells are more similar in genetics and biological content to the human brain cells than other animal disease models. However, culture of neuronal cells in assay plates requires a labor-intensive procedure of plate pre-coating, hampering its applications in highthroughput screening (HTS). We developed a simplified method with one-step seeding of neural stem cells in assay plates by supplementing the medium with a recombinant human vitronectin (VTN), thus avoiding plate pre-coating. Robust results were obtained from cell viability, calcium response, and neurite outgrowth assays using this new method. Our data demonstrate that this approach greatly simplifies highthroughput assays using neuronal cells differentiated from human stem cells for translational research. PMID:27647668

A new non-viral method of gene transfection was designed to enhance the level of gene expression for rat mesenchymal stem cells (MSCs). Pullulan was cationized using chemical introduction of spermine to prepare cationized pullulan of non-viral carrier (spermine-pullulan). The spermine-pullulan was complexed with a plasmid deoxyribonucleic acid (DNA) of luciferase and coated on the surface of culture substrate together with Pronectin of artificial cell adhesion protein. MSCs were cultured and transfected on the complex-coated substrate (reverse transfection), and the level and duration of gene expression were compared with those of MSCs transfected by culturing in the medium containing the plasmid DNA-spermine-pullulan complex (conventional method). The reverse transfection method enhanced and prolonged gene expression significantly more than did the conventional method. The reverse method permitted the transfection culture of MSCs in the presence of serum, in contrast to the conventional method, which gave cells a good culture condition to lower cytotoxicity. The reverse transfection was carried out for a non-woven fabric of polyethylene terephthalate (PET) coated with the complex and Pronectin using agitation and stirring culture methods. The two methods enhanced the level and duration of gene expression for MSCs significantly more than did the static method. It is possible that medium circulation improves the culture conditions of cells in terms of oxygen and nutrition supply and waste excretion, resulting in enhanced gene expression.

Background The cabbage, Brassica oleracea var. capitata L., has a distinguishable phenotype within the genus Brassica. Despite the economic and genetic importance of cabbage, there is little genomic data for cabbage, and most studies of Brassica are focused on other species or other B. oleracea subspecies. The lack of genomic data for cabbage, a non-model organism, hinders research on its molecular biology. Hence, the construction of reliable transcriptomic data based on high-throughput sequencing technologies is needed to enhance our understanding of cabbage and provide genomic information for future work. Methodology/Principal Findings We constructed cDNAs from total RNA isolated from the roots, leaves, flowers, seedlings, and calcium-limited seedling tissues of two cabbage genotypes: 102043 and 107140. We sequenced a total of six different samples using the Illumina HiSeq platform, producing 40.5 Gbp of sequence data comprising 401,454,986 short reads. We assembled 205,046 transcripts (≥ 200 bp) using the Velvet and Oases assembler and predicted 53,562 loci from the transcripts. We annotated 35,274 of the loci with 55,916 plant peptides in the Phytozome database. The average length of the annotated loci was 1,419 bp. We confirmed the reliability of the sequencing assembly using reverse-transcriptase PCR to identify tissue-specific gene candidates among the annotated loci. Conclusion Our study provides valuable transcriptome sequence data for B. oleracea var. capitata L., offering a new resource for studying B. oleracea and closely related species. Our transcriptomic sequences will enhance the quality of gene annotation and functional analysis of the cabbage genome and serve as a material basis for future genomic research on cabbage. The sequencing data from this study can be used to develop molecular markers and to identify the extreme differences among the phenotypes of different species in the genus Brassica. PMID:24682075

The ease of genetic manipulation, low cost, rapid growth and number of previous studies have made Escherichia coli one of the most widely used microorganism species for producing recombinant proteins. In this post-genomic era, challenges remain to rapidly express and purify large numbers of proteins for academic and commercial purposes in a high-throughput manner. In this review, we describe several state-of-the-art approaches that are suitable for the cloning, expression and purification, conducted in parallel, of numerous molecules, and we discuss recent progress related to soluble protein expression, mRNA folding, fusion tags, post-translational modification and production of membrane proteins. Moreover, we address the ongoing efforts to overcome various challenges faced in protein expression in E. coli, which could lead to an improvement of the current system from trial and error to a predictable and rational design. PMID:27581654

We present DevStaR, an automated computer vision and machine learning system that provides rapid, accurate, and quantitative measurements of C. elegans embryonic viability in high-throughput (HTP) applications. A leading genetic model organism for the study of animal development and behavior, C. elegans is particularly amenable to HTP functional genomic analysis due to its small size and ease of cultivation, but the lack of efficient and quantitative methods to score phenotypes has become a major bottleneck. DevStaR addresses this challenge using a novel hierarchical object recognition machine that rapidly segments, classifies, and counts animals at each developmental stage in images of mixed-stage populations of C. elegans. Here, we describe the algorithmic design of the DevStaR system and demonstrate its performance in scoring image data acquired in HTP screens.

Ethanol production by microorganisms is an important renewable energy source. Most processes involve fermentation of sugars from plant feedstock, but there is increasing interest in direct ethanol production by photosynthetic organisms. To facilitate this, a high-throughput screening technique for the detection of ethanol is required. Here, a method for the quantitative detection of ethanol in a microdroplet-based platform is described that can be used for screening cyanobacterial strains to identify those with the highest ethanol productivity levels. The detection of ethanol by enzymatic assay was optimized both in bulk and in microdroplets. In parallel, the encapsulation of engineered ethanol-producing cyanobacteria in microdroplets and their growth dynamics in microdroplet reservoirs were demonstrated. The combination of modular microdroplet operations including droplet generation for cyanobacteria encapsulation, droplet re-injection and pico-injection, and laser-induced fluorescence, were used to create this new platform to screen genetically engineered strains of cyanobacteria with different levels of ethanol production.

Completion of the Human Genome Project and the HapMap Project has led to increasing demands for mapping complex traits in humans to understand the aetiology of diseases. Identifying variations in the DNA sequence, which affect how we develop disease and respond to pathogens and drugs, is important for this purpose, but it is difficult to identify these variations in large sample sets. Here we show that through a combination of capillary sequencing and polymerase chain reaction assisted by gold nanoparticles, it is possible to identify several DNA variations that are associated with age-related macular degeneration and psoriasis on significant regions of human genomic DNA. Our method is accurate and promising for large-scale and high-throughputgenetic analysis of susceptibility towards disease and drug resistance.

Plasma membrane proteins are essential molecules in the cell which mediate interactions with the exterior milieu, thus representing key drug targets for present pharma. Not surprisingly, protein traffic disorders include a large range of diseases sharing the common mechanism of failure in the respective protein to reach the plasma membrane. However, specific therapies for these diseases are remarkably lacking. Herein, we report a robust platform for drug discovery applied to a paradigmatic genetic disorder affecting intracellular trafficking – Cystic Fibrosis. This platform includes (i) two original respiratory epithelial cellular models incorporating an inducible double-tagged traffic reporter; (ii) a plasma membrane protein traffic assay for high-throughput microscopy screening; and (iii) open-source image analysis software to quantify plasma membrane protein traffic. By allowing direct scoring of compounds rescuing the basic traffic defect, this platform enables an effective drug development pipeline, which can be promptly adapted to any traffic disorder-associated protein and leverage therapy development efforts. PMID:25762484

The increasing use of zebrafish larvae for biomedical research applications is resulting in versatile models for a variety of human diseases. These models exploit the optical transparency of zebrafish larvae and the availability of a large genetic tool box. Here we present detailed protocols for the robotic injection of zebrafish embryos at very high accuracy with a speed of up to 2000 embryos per hour. These protocols are benchmarked for several applications: (1) the injection of DNA for obtaining transgenic animals, (2) the injection of antisense morpholinos that can be used for gene knock-down, (3) the injection of microbes for studying infectious disease, and (4) the injection of human cancer cells as a model for tumor progression. We show examples of how the injected embryos can be screened at high-throughput level using fluorescence analysis. Our methods open up new avenues for the use of zebrafish larvae for large compound screens in the search for new medicines.

Caenorhabditis elegans postembryonic development consists of four discrete larval stages separated by molts. Typically, the speed of progression through these larval stages is investigated by visual inspection of the molting process. Here, we describe an automated method to monitor the timing of these discrete phases of C. elegans maturation, from the first larval stage through adulthood, using bioluminescence. The method was validated with a lin-42 mutant strain that shows delayed development relative to wild-type animals and with a daf-2 mutant that shows an extended second larval stage. This new method is inherently high-throughput and will finally allow dissecting the molecular machinery governing the speed of the developmental clock, which has so far been hampered by the lack of a method suitable for genetic screens. PMID:26294666

Caenorhabditis elegans postembryonic development consists of four discrete larval stages separated by molts. Typically, the speed of progression through these larval stages is investigated by visual inspection of the molting process. Here, we describe an automated method to monitor the timing of these discrete phases of C. elegans maturation, from the first larval stage through adulthood, using bioluminescence. The method was validated with a lin-42 mutant strain that shows delayed development relative to wild-type animals and with a daf-2 mutant that shows an extended second larval stage. This new method is inherently high-throughput and will finally allow dissecting the molecular machinery governing the speed of the developmental clock, which has so far been hampered by the lack of a method suitable for genetic screens.

High-throughput phenotyping produces multiple measurements over time, which require new methods of analyses that are flexible in their quantification of plant growth and transpiration, yet are computationally economic. Here we develop such analyses and apply this to a rice population genotyped with a 700k SNP high-density array. Two rice diversity panels, indica and aus, containing a total of 553 genotypes, are phenotyped in waterlogged conditions. Using cubic smoothing splines to estimate plant growth and transpiration, we identify four time intervals that characterize the early responses of rice to salinity. Relative growth rate, transpiration rate and transpiration use efficiency (TUE) are analysed using a new association model that takes into account the interaction between treatment (control and salt) and genetic marker. This model allows the identification of previously undetected loci affecting TUE on chromosome 11, providing insights into the early responses of rice to salinity, in particular into the effects of salinity on plant growth and transpiration. PMID:27853175

Technologies for handling, sorting, and positioning of embryos are increasingly important in biomedicine. In this paper the status for ongoing projects aimed at developing instrumentation for high-throughput treatment of embryos is reviewed. Techniques for positioning of Drosophila (fruit-fly) embryos in 2-D arrays for use in microinjection experiments are especially focused. A method based on fluidic micro assembly is discussed, and important parameters such as immobilization yield, the number of misplaced embryos, and adhesion force of the embryos are reported. A model for the assembly process is described, and simulation results are in good agreement with adhesion force measurements. A fully automated MEMS based system for fruit-fly embryo injection has recently been demonstrated at Stanford University. The first experiments with double-stranded RNA injection proved successful, and the expected genetic modification of the embryos was observed.

Purpose. Retinal dystrophy (RD) is a broad group of hereditary disorders with heterogeneous genotypes and phenotypes. Current available genetic testing for these diseases is complicated, time consuming, and expensive. This study was conducted to develop and apply a microarray-based, high-throughput resequencing system to detect sequence alterations in genes related to inherited RD. Methods. A customized 300-kb resequencing chip, Retina-Array, was developed to detect sequence alterations of 267,550 bases of both sense and antisense sequence in 1470 exons spanning 93 genes involved in inherited RD. Retina-Array was evaluated in 19 patient samples with inherited RD provided by the eyeGENE repository and four Centre d'Etudes du Polymorphisme Humaine reference samples through a high-throughput experimental approach that included an automated PCR assay setup and quantification, efficient post-quantification data processing, optimized pooling and fragmentation, and standardized chip processing. Results. The performance of the chips demonstrated that the average base pair call rate and accuracy were 93.56% and 99.86%, respectively. In total, 304 candidate variations were identified using a series of customized screening filters. Among 174 selected variations, 123 (70.7%) were further confirmed by dideoxy sequencing. Analysis of patient samples using Retina-Array resulted in the identification of 10 known mutations and 12 novel variations with high probability of deleterious effects. Conclusions. This study suggests that Retina-Array might be a valuable tool for the detection of disease-causing mutations and disease severity modifiers in a single experiment. Retinal-Array may provide a powerful and feasible approach through which to study genetic heterogeneity in retinal diseases. PMID:22025579

Germplasm collections provide an extremely valuable resource for breeders and researchers. However, misclassification of accessions by species often hinders the effective use of these collections. We propose that use of high-throughput genotyping tools can provide a fast, efficient and cost-effective way of confirming species in germplasm collections, as well as providing valuable genetic diversity data. We genotyped 180 Brassicaceae samples sourced from the Australian Grains Genebank across the recently released Illumina Infinium Brassica 60K SNP array. Of these, 76 were provided on the basis of suspected misclassification and another 104 were sourced independently from the germplasm collection. Presence of the A- and C-genomes combined with principle components analysis clearly separated Brassica rapa, B. oleracea, B. napus, B. carinata and B. juncea samples into distinct species groups. Several lines were further validated using chromosome counts. Overall, 18% of samples (32/180) were misclassified on the basis of species. Within these 180 samples, 23/76 (30%) supplied on the basis of suspected misclassification were misclassified, and 9/105 (9%) of the samples randomly sourced from the Australian Grains Genebank were misclassified. Surprisingly, several individuals were also found to be the product of interspecific hybridization events. The SNP (single nucleotide polymorphism) array proved effective at confirming species, and provided useful information related to genetic diversity. As similar genomic resources become available for different crops, high-throughput molecular genotyping will offer an efficient and cost-effective method to screen germplasm collections worldwide, facilitating more effective use of these valuable resources by breeders and researchers.

To dissect the genetic basis of dynamic adaptive traits under relevant growing conditions, we employed a field-based, high-throughput plant phenotyping (HTPP) system that deployed four sets of sensors to simultaneously measure canopy temperature, reflectance, and height on a cotton (Gossypium hirsut...

Spo11 is the topoisomerase-like enzyme responsible for the induction of the meiosis-specific double strand breaks (DSBs), which initiates the recombination events responsible for proper chromosome segregation. Nineteen PCR-induced alleles of SPO11 were identified and characterized genetically and cytologically. Recombination, spore viability and synaptonemal complex (SC) formation were decreased to varying extents in these mutants. Arrest by ndt80 restored these events in two severe hypomorphic mutants, suggesting that ndt80-arrested nuclei are capable of extended DSB activity. While crossing-over, spore viability and synaptonemal complex (SC) formation defects correlated, the extent of such defects was not predictive of the level of heteroallelic gene conversions (prototrophs) exhibited by each mutant. Highthroughput sequencing of tetrads from spo11 hypomorphs revealed that gene conversion tracts associated with COs are significantly longer and gene conversion tracts unassociated with COs are significantly shorter than in wild type. By modeling the extent of these tract changes, we could account for the discrepancy in genetic measurements of prototrophy and crossover association. These findings provide an explanation for the unexpectedly low prototroph levels exhibited by spo11 hypomorphs and have important implications for genetic studies that assume an unbiased recovery of prototrophs, such as measurements of CO homeostasis. Our genetic and physical data support previous observations of DSB-limited meioses, in which COs are disproportionally maintained over NCOs (CO homeostasis).

Most species of penguins are sexual monomorphic and therefore it is difficult to visually identify their genders for monitoring population stability in terms of sex ratio analysis. In this study, we evaluated the suitability using melting curve analysis (MCA) for high-throughput gender identification of penguins. Preliminary test indicated that the Griffiths's P2/P8 primers were not suitable for MCA analysis. Based on sequence alignment of Chromo-Helicase-DNA binding protein (CHD)-W and CHD-Z genes from four species of penguins (Pygoscelis papua, Aptenodytes patagonicus, Spheniscus magellanicus, and Eudyptes chrysocome), we redesigned forward primers for the CHD-W/CHD-Z-common region (PGU-ZW2) and the CHD-W-specific region (PGU-W2) to be used in combination with the reverse Griffiths's P2 primer. When tested with P. papua samples, PCR using P2/PGU-ZW2 and P2/PGU-W2 primer sets generated two amplicons of 148- and 356-bp, respectively, which were easily resolved in 1.5% agarose gels. MCA analysis indicated the melting temperature (Tm) values for P2/PGU-ZW2 and P2/PGU-W2 amplicons of P. papua samples were 79.75°C-80.5°C and 81.0°C-81.5°C, respectively. Females displayed both ZW-common and W-specific Tm peaks, whereas male was positive only for ZW-common peak. Taken together, our redesigned primers coupled with MCA analysis allows precise highthroughput gender identification for P. papua, and potentially for other penguin species such as A. patagonicus, S. magellanicus, and E. chrysocome as well.

Chromatographic separation serves as "a workhorse" for downstream process development and plays a key role in removal of product-related, host cell-related, and process-related impurities. Complex and poorly characterized raw materials and feed material, low feed concentration, product instability, and poor mechanistic understanding of the processes are some of the critical challenges that are faced during development of a chromatographic step. Traditional process development is performed as trial-and-error-based evaluation and often leads to a suboptimal process. High-throughput process development (HTPD) platform involves an integration of miniaturization, automation, and parallelization and provides a systematic approach for time- and resource-efficient chromatography process development. Creation of such platforms requires integration of mechanistic knowledge of the process with various statistical tools for data analysis. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today. This protocol describes the steps involved in performing HTPD of process chromatography step. It described operation of a commercially available device (PreDictor™ plates from GE Healthcare). This device is available in 96-well format with 2 or 6 μL well size. We also discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that is gathered from such a platform. A case study involving use of the protocol for examining ion-exchange chromatography of granulocyte colony-stimulating factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that is representative of the data obtained at the traditional lab scale. The agreement in the

We report on a micromachined silicon chip that is capable of providing a high-throughput functional assay based on calorimetry. A prototype twin microcalorimeter based on the Seebeck effect has been fabricated by IC technology and micromachined postprocessing techniques. A biocompatible liquid rubber membrane supports two identical 0.5 X 2 cm2 measurement chambers, situated at the cold and hot junction of a 666-junction aluminum/p+-polysilicon thermopile. The chambers can house up to 106 eukaryotic cells cultured to confluence. The advantage of the device over microcalorimeters on the market, is the integration of the measurement channels on chip, rendering microvolume reaction vessels, ranging from 10 to 600 (mu) l, in the closest possible contact with the thermopile sensor (no springs are needed). Power and temperature sensitivity of the sensor are 23 V/W and 130 mV/K, respectively. The small thermal inertia of the microchannels results in the short response time of 70 s, when filled with 50 (mu) l of water. Biological experiments were done with cultured kidney cells of Xenopus laevis (A6). The thermal equilibration time of the device is 45 min. Stimulation of transport mechanisms by reducing bath osmolality by 50% increased metabolism by 20%. Our results show that it is feasible to apply this large-area, small- volume whole-cell biosensor for drug discovery, where the binding assays that are commonly used to provide high- throughput need to be complemented with a functional assay. Solutions are brought onto the sensor by a simple pipette, making the use of an industrial microtiterplate dispenser feasible on a nx96-array of the microcalorimeter biosensor. Such an array of biosensors has been designed based on a new set of requirements as set forth by people in the field as this project moved on. The results obtained from the prototype large-area sensor were used to obtain an accurate model of the calorimeter, checked for by the simulation software ANSYS. At

Recent developments in digital video, multimedia technology and data networks have greatly increased the demand for high bandwidth communication channels and highthroughput data processing. Electronics is particularly suited for switching, amplification and logic functions, while optics is more suitable for interconnections and communications with lower energy and crosstalk. In this research, we present the design, testing, integration and demonstration of several optoelectronic smart pixel devices and system architectures. These systems integrate electronic switching/processing capability with parallel optical interconnections to provide highthroughput network communication and pipeline data processing. The Smart Pixel Array Cellular Logic processor (SPARCL) is designed in 0.8 m m CMOS and hybrid integrated with Multiple-Quantum-Well (MQW) devices for pipeline image processing. The Smart Pixel Network Interface (SAPIENT) is designed in 0.6 m m GaAs and monolithically integrated with LEDs to implement a highly parallel optical interconnection network. The Translucent Smart Pixel Array (TRANSPAR) design is implemented in two different versions. The first version, TRANSPAR-MQW, is designed in 0.5 m m CMOS and flip-chip integrated with MQW devices to provide 2-D pipeline processing and translucent networking using the Carrier- Sense-MultipleAccess/Collision-Detection (CSMA/CD) protocol. The other version, TRANSPAR-VM, is designed in 1.2 m m CMOS and discretely integrated with VCSEL-MSM (Vertical-Cavity-Surface- Emitting-Laser and Metal-Semiconductor-Metal detectors) chips and driver/receiver chips on a printed circuit board. The TRANSPAR-VM provides an option of using the token ring network protocol in addition to the embedded functions of TRANSPAR-MQW. These optoelectronic smart pixel systems also require micro-optics devices to provide high resolution, high quality optical interconnections and external source arrays. In this research, we describe an innovative

HEVC (High Efficiency Video Coding) is the next-generation video coding standard being jointly developed by the ITU-T VCEG and ISO/IEC MPEG JCT-VC team. In addition to the high coding efficiency, which is expected to provide 50% more bit-rate reduction when compared to H.264/AVC, HEVC has built-in parallel processing tools to address bitrate, pixel-rate and motion estimation (ME) throughput requirements. This paper describes how CABAC, which is also used in H.264/AVC, has been redesigned for improved throughput, and how parallel merge/skip and tiles, which are new tools introduced for HEVC, enable high-throughput processing. CABAC has data dependencies which make it difficult to parallelize and thus limit its throughput. The prediction error/residual, represented as quantized transform coefficients, accounts for the majority of the CABAC workload. Various improvements have been made to the context selection and scans in transform coefficient coding that enable CABAC in HEVC to potentially achieve higher throughput and increased coding gains relative to H.264/AVC. The merge/skip mode is a coding efficiency enhancement tool in HEVC; the parallel merge/skip breaks dependency between the regular and merge/skip ME, which provides flexibility for highthroughput and high efficiency HEVC encoder designs. For ultra high definition (UHD) video, such as 4kx2k and 8kx4k resolutions, low-latency and real-time processing may be beyond the capability of a single core codec. Tiles are an effective tool which enables pixel-rate balancing among the cores to achieve parallel processing with a throughput scalable implementation of multi-core UHD video codec. With the evenly divided tiles, a multi-core video codec can be realized by simply replicating single core codec and adding a tile boundary processing core on top of that. These tools illustrate that accounting for implementation cost when designing video coding algorithms can enable higher processing speed and reduce

Experimental evolution is a powerful tool for investigating complex traits. Artificial selection can be applied for a specific trait and the resulting phenotypically divergent populations pool-sequenced to identify alleles that occur at substantially different frequencies in the extreme populations. To maximize the proportion of loci that are causal to the phenotype among all enriched loci, population size and number of replicates need to be high. These requirements have, in fact, limited evolution studies in higher organisms, where the time investment required for phenotyping is often prohibitive for large-scale studies. Animal size is a highly multigenic trait that remains poorly understood, and an experimental evolution approach may thus aid in gaining new insights into the genetic basis of this trait. To this end, we developed the FlyCatwalk, a fully automated, high-throughput system to sort live fruit flies (Drosophila melanogaster) based on morphometric traits. With the FlyCatwalk, we can detect gender and quantify body and wing morphology parameters at a four-old higher throughput compared with manual processing. The phenotyping results acquired using the FlyCatwalk correlate well with those obtained using the standard manual procedure. We demonstrate that an automated, high-throughput, feature-based sorting system is able to avoid previous limitations in population size and replicate numbers. Our approach can likewise be applied for a variety of traits and experimental settings that require high-throughput phenotyping. PMID:25556112

Arrayed genetic screens mediated by the CRISPR/Cas9 technology with single guide RNA (sgRNA) libraries demand a high-throughput platform capable of transfecting diverse cell types at a high efficiency in a genome-wide scale for detection and analysis of sophisticated cellular phenotypes. Here we developed a high-throughput in situ cell electroporation (HiCEP) microsystem which leveraged the superhydrophobic feature of the microwell array to achieve individually controlled conditions in each microwell and coupled an interdigital electrode array chip with the microwells in a modular-based scheme for highly efficient delivery of exogenous molecules into cells. Two plasmids encoding enhanced green and red fluorescent proteins (EGFP and ERFP), respectively, were successfully electroporated into attached HeLa cells on a 169-microwell array chip with transfection efficiencies of 71.6 ± 11.4% and 62.9 ± 2.7%, and a cell viability above 95%. We also successfully conducted selective electroporation of sgRNA into 293T cells expressing the Cas9 nuclease in a high-throughput manner and observed the four-fold increase of the GFP intensities due to the repair of the protein coding sequences mediated by the CRISPR/Cas9 system. This study proved that this HiCEP system has the great potential to be used for arrayed functional screens with genome-wide CRISPR libraries on hard-to-transfect cells in the future. PMID:28211892

Experimental evolution is a powerful tool for investigating complex traits. Artificial selection can be applied for a specific trait and the resulting phenotypically divergent populations pool-sequenced to identify alleles that occur at substantially different frequencies in the extreme populations. To maximize the proportion of loci that are causal to the phenotype among all enriched loci, population size and number of replicates need to be high. These requirements have, in fact, limited evolution studies in higher organisms, where the time investment required for phenotyping is often prohibitive for large-scale studies. Animal size is a highly multigenic trait that remains poorly understood, and an experimental evolution approach may thus aid in gaining new insights into the genetic basis of this trait. To this end, we developed the FlyCatwalk, a fully automated, high-throughput system to sort live fruit flies (Drosophila melanogaster) based on morphometric traits. With the FlyCatwalk, we can detect gender and quantify body and wing morphology parameters at a four-old higher throughput compared with manual processing. The phenotyping results acquired using the FlyCatwalk correlate well with those obtained using the standard manual procedure. We demonstrate that an automated, high-throughput, feature-based sorting system is able to avoid previous limitations in population size and replicate numbers. Our approach can likewise be applied for a variety of traits and experimental settings that require high-throughput phenotyping.

Transglutaminases (TGs) are widely distributed enzymes that catalyze posttranslational modification of proteins by Ca(2+)-dependent cross-linking reactions. The family members of TGs participate in many significant processes of biological functions such as tissue regeneration, cell differentiation, apoptosis, and certain pathologies. A novel technique for TG activity assay was developed in this study. It was based on the rapid capturing, fluorescence quenching, and fast separation of the unreacted fluorescent molecules from the macromolecular product with magnetic dextran-coated charcoal. As few as 3 ng of guinea pig liver transglutaminase (gpTG) could be detected by the method; activities of 96 TG samples could be measured within an hour. The K(m) of gpTG determined by this method for monodansylcadaverine (dansyl-CAD) and N, N-dimethylcasein was 14 and 5 muM, respectively. A typical competitive inhibition pattern of cystamine on dansyl-CAD for gpTG activity was also demonstrated. The application of this technique is not limited to the use of dansyl-CAD as the fluorescent substrate of TG; other small fluor-labeled TG substrates may substitute dansyl-CAD. Finally, this method is rapid, highly sensitive, and inexpensive. It is suitable not only for high-throughput screening of enzymes or enzyme inhibitors but also for enzyme kinetic analysis.

Structural health monitoring (SHM) using wireless smart sensors (WSS) has the potential to provide rich information on the state of a structure. However, because of their distributed nature, maintaining highly robust and reliable networks can be challenging. Assessing WSS network communication quality before and after finalizing a deployment is critical to achieve a successful WSS network for SHM purposes. Early studies on WSS network reliability mostly used temporal signal indicators, composed of a smaller number of packets, to assess the network reliability. However, because the WSS networks for SHM purpose often require high data throughput, i.e., a larger number of packets are delivered within the communication, such an approach is not sufficient. Instead, in this study, a model that can assess, probabilistically, the long-term performance of the network is proposed. The proposed model is based on readily-available measured data sets that represent communication quality during high-throughput data transfer. Then, an empirical limit-state function is determined, which is further used to estimate the probability of network communication failure. Monte Carlo simulation is adopted in this paper and applied to a small and a full-bridge wireless networks. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved. PMID:27258270

AVA Solar has developed a very low cost solar photovoltaic (PV) manufacturing process and has demonstrated the significant economic and commercial potential of this technology. This I & I Category 3 project provided significant assistance toward accomplishing these milestones. The original goals of this project were to design, construct and test a production prototype system, fabricate PV modules and test the module performance. The original module manufacturing costs in the proposal were estimated at $2/Watt. The objectives of this project have been exceeded. An advanced processing line was designed, fabricated and installed. Using this automated, highthroughput system, high efficiency devices and fully encapsulated modules were manufactured. AVA Solar has obtained 2 rounds of private equity funding, expand to 50 people and initiated the development of a large scale factory for 100+ megawatts of annual production. Modules will be manufactured at an industry leading cost which will enable AVA Solar's modules to produce power that is cost-competitive with traditional energy resources. With low manufacturing costs and the ability to scale manufacturing, AVA Solar has been contacted by some of the largest customers in the PV industry to negotiate long-term supply contracts. The current market for PV has continued to grow at 40%+ per year for nearly a decade and is projected to reach $40-$60 Billion by 2012. Currently, a crystalline silicon raw material supply shortage is limiting growth and raising costs. Our process does not use silicon, eliminating these limitations.

When a disk of filter paper is impregnated with a cytotoxic or cytostatic drug and added to solid medium seeded with yeast, a visible clear zone forms around the disk whose size depends on the concentration and potency of the drug. This is the traditional "halo" assay and provides a convenient, if low-throughput, read-out of biological activity that has been the mainstay of antifungal and antibiotic testing for decades. Here, we describe a protocol for a high-throughput version of the halo assay, which uses an array of 384 pins to deliver ∼200 nL of stock solutions from compound plates onto single-well plates seeded with yeast. Using a plate reader in the absorbance mode, the resulting halos can be quantified and the data archived in the form of flat files that can be connected to compound databases with standard software. This assay has the convenience associated with the visual readout of the traditional halo assay but uses far less material and can be automated to screen thousands of compounds per day.

Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing’s outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a highthroughput approach appropriate for massive data extraction from food samples. PMID:26466349

A common thread throughout the clinical and translational research domains is the need to collect, manage, integrate, analyze, and disseminate large-scale, heterogeneous biomedical data sets. However, well-established and broadly adopted theoretical and practical frameworks and models intended to address such needs are conspicuously absent in the published literature or other reputable knowledge sources. Instead, the development and execution of multidisciplinary, clinical, or translational studies are significantly limited by the propagation of “silos” of both data and expertise. Motivated by this fundamental challenge, we report upon the current state and evolution of biomedical informatics as it pertains to the conduct of high-throughput clinical and translational research and will present both a conceptual and practical framework for the design and execution of informatics-enabled studies. The objective of presenting such findings and constructs is to provide the clinical and translational research community with a common frame of reference for discussing and expanding upon such models and methodologies. PMID:19737991

High-throughput screening (HTS) for potential thyroid–disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limited in the US EPA ToxCast screening assay portfolio. To fill one critical screening gap, the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay was developed to identify chemicals that inhibit TPO, as decreased TPO activity reduces TH synthesis. The ToxCast Phase I and II chemical libraries, comprised of 1,074 unique chemicals, were initially screened using a single, high concentration to identify potential TPO inhibitors. Chemicals positive in the single concentration screen were retested in concentration-response. Due to high false positive rates typically observed with loss-of-signal assays such as AUR-TPO, we also employed two additional assays in parallel to identify possible sources of nonspecific assay signal loss, enabling stratification of roughly 300 putative TPO inhibitors based upon selective AUR-TPO activity. A cell-free luciferase inhibition assay was used to identify nonspecific enzyme inhibition among the putative TPO inhibitors, and a cytotoxicity assay using a human cell line was used to estimate the cellular tolerance limit. Additionally, the TPO inhibition activities of 150 chemicals were compared between the AUR-TPO and an orthogonal peroxidase oxidation assay using

The National Research Council of the United States National Academies of Science has recently released a document outlining a long-range vision and strategy for transforming toxicity testing from largely whole animal-based testing to one based on in vitro assays. “Toxicity Testing in the 21st Century: A Vision and a Strategy” advises a focus on relevant human toxicity pathway assays. Toxicity pathways are defined in the document as “Cellular response pathways that, when sufficiently perturbed, are expected to result in adverse health effects”. Results of such pathway screens would serve as a filter to drive selection of more specific, targeted testing that will complement and validate the pathway assays. In response to this report, the US EPA has partnered with two NIH organizations, the National Toxicology Program and the NIH Chemical Genomics Center (NCGC), in a program named Tox21. A major goal of this collaboration is to screen chemical libraries consisting of known toxicants, chemicals of environmental and occupational exposure concern, and human pharmaceuticals in cell-based pathway assays. Currently, approximately 3000 compounds (increasing to 9000 by the end of 2009) are being validated and screened in quantitative high-throughput (qHTS) format at the NCGC producing extensive concentration-response data for a diverse set of potential toxicity pathways. The Tox21 collaboration is extremely interested in accessing additional toxicity pathway assa

File-transfer rates for ftp are often reported to be relatively slow, compared to the raw bandwidth available in emerging gigabit networks. While a major bottleneck is disk I/O, protocol issues impact performance as well. Ftp was developed and optimized for use over the TCP/IP protocol stack of the Internet. However, TCP has been shown to run inefficiently over ATM. In an effort to maximize network throughput, data-transfer protocols can be developed to run over UDP or directly over IP, rather than over TCP. If error-free transmission is required, techniques for achieving reliable transmission can be included as part of the transfer protocol. However, selected image-processing applications can tolerate a low level of errors in images that are transmitted over a network. In this paper we report on experimental work to develop a high-throughput protocol for unreliable data transfer over ATM networks. We attempt to maximize throughput by keeping the communications pipe full, but still keep packet loss under five percent. We use the Bay Area Gigabit Network Testbed as our experimental platform.

Cell sorting is an important screening process in microbiology, biotechnology, and clinical research. Existing methods are mainly based on single-cell analysis as in flow cytometric and microfluidic cell sorters. Here we report a label-free bulk method for sorting cells by differentiating their characteristic surface free energies (SFEs). We demonstrated the feasibility of this method by sorting model binary cell mixtures of various bacterial species, including Pseudomonas putida KT2440, Enterococcus faecalis ATCC 29212, Salmonella Typhimurium ATCC 14028, and Escherichia coli DH5α. This method can effectively separate 10(10) bacterial cells within 30 min. Individual bacterial species can be sorted with up to 96% efficiency, and the cell viability ratio can be as high as 99%. In addition to its capacity of sorting evenly mixed bacterial cells, we demonstrated the feasibility of this method in selecting and enriching cells of minor populations in the mixture (presenting at only 1% in quantity) to a purity as high as 99%. This SFE-activated method may be used as a stand-alone method for quickly sorting a large quantity of bacterial cells or as a prescreening tool for microbial discrimination. Given its advantages of label-free, high-throughput, low cost, and simplicity, this SFE-activated cell sorting method has potential in various applications of sorting cells and abiotic particles.

A novel, simple geometry for highthroughput electrospinning from a bowl edge is presented that utilizes a vessel filled with a polymer solution and a concentric cylindrical collector. Successful fiber formation is presented for two different polymer systems with differing solution viscosity and solvent volatility. The process of jet initiation, resultant fiber morphology and fiber production rate are discussed for this unconfined feed approach. Under high voltage initiation, the jets spontaneously form directly on the fluid surface and rearrange along the circumference of the bowl to provide approximately equal spacing between spinning sites. Nanofibers currently produced from bowl electrospinning are identical in quality to those fabricated by traditional needle electrospinning (TNE) with a demonstrated ~ 40 times increase in the production rate for a single batch of solution due primarily to the presence of many simultaneous jets. In the bowl electrospinning geometry, the electric field pattern and subsequent effective feed rate are very similar to those parameters found under optimized TNE experiments. Consequently, the electrospinning process per jet is directly analogous to that in TNE and thereby results in the same quality of nanofibers.

The attenuation of sedimentation and convection in microgravity can sometimes decrease irregularities formed during macromolecular crystal growth. Current terrestrial protein crystal growth (PCG) capabilities are very different than those used during the Shuttle era and that are currently on the International Space Station (ISS). The focus of this experiment was to demonstrate the use of a commercial off-the-shelf, highthroughput, PCG method in microgravity. Using Protein BioSolutions’ microfluidic Plug Maker™/CrystalCard™ system, we tested the ability to grow crystals of the regulator of glucose metabolism and adipogenesis: peroxisome proliferator-activated receptor gamma (apo-hPPAR-γ LBD), as well as several PCG standards. Overall, we sent 25 CrystalCards™ to the ISS, containing ~10,000 individual microgravity PCG experiments in a 3U NanoRacks NanoLab (1U = 103 cm.). After 70 days on the ISS, our samples were returned with 16 of 25 (64%) microgravity cards having crystals, compared to 12 of 25 (48%) of the ground controls. Encouragingly, there were more apo-hPPAR-γ LBD crystals in the microgravity PCG cards than the 1g controls. These positive results hope to introduce the use of the PCG standard of low sample volume and large experimental density to the microgravity environment and provide new opportunities for macromolecular samples that may crystallize poorly in standard laboratories. PMID:24278480

Highthroughput sequencing (HTS) generates large amounts of high quality sequence data for microbial genomics. The value of HTS for microbial forensics is the speed at which evidence can be collected and the power to characterize microbial-related evidence to solve biocrimes and bioterrorist events. As HTS technologies continue to improve, they provide increasingly powerful sets of tools to support the entire field of microbial forensics. Accurate, credible results allow analysis and interpretation, significantly influencing the course and/or focus of an investigation, and can impact the response of the government to an attack having individual, political, economic or military consequences. Interpretation of the results of microbial forensic analyses relies on understanding the performance and limitations of HTS methods, including analytical processes, assays and data interpretation. The utility of HTS must be defined carefully within established operating conditions and tolerances. Validation is essential in the development and implementation of microbial forensics methods used for formulating investigative leads attribution. HTS strategies vary, requiring guiding principles for HTS system validation. Three initial aspects of HTS, irrespective of chemistry, instrumentation or software are: 1) sample preparation, 2) sequencing, and 3) data analysis. Criteria that should be considered for HTS validation for microbial forensics are presented here. Validation should be defined in terms of specific application and the criteria described here comprise a foundation for investigators to establish, validate and implement HTS as a tool in microbial forensics, enhancing public safety and national security. PMID:25101166

Highly integrated hybridization assay and capillary electrophoresis have improved the throughput of DNA analysis. The shift to highthroughput analysis requires a high speed DNA amplification system, and several rapid PCR systems have been developed. In these thermal cyclers, the temperature was controlled by effective methodology instead of a large heating/cooling block preventing rapid thermal cycling. In our research, high speed PCR was performed using a silicon-based microchamber array and three heat blocks. The highly integrated microchamber array was fabricated by semiconductor microfabrication techniques. The temperature of the PCR microchamber was controlled by alternating between three heat blocks of different temperature. In general, silicon has excellent thermal conductivity, and the heat capacity is small in the miniaturized sample volume. Hence, the heating/cooling rate was rapid, approximately 16 degrees C/s. The rapid PCR was therefore completed in 18 min for 40 cycles. The thermal cycle time was reduced to 1/10 of a commercial PCR instrument (Model 9600, PE Applied Biosystems-3 h).

One of the main stumbling blocks encountered when attempting to express foreign proteins in Escherichia coli is the occurrence of amorphous aggregates of misfolded proteins, called inclusion bodies (IB). Developing efficient protein native structure recovery procedures based on IB refolding is therefore an important challenge. Unfortunately, there is no "universal" refolding buffer: Experience shows that refolding buffer composition varies from one protein to another. In addition, the methods developed so far for finding a suitable refolding buffer suffer from a number of weaknesses. These include the small number of refolding formulations, which often leads to negative results, solubility assays incompatible with high-throughput, and experiment formatting not suitable for automation. To overcome these problems, it was proposed in the present study to address some of these limitations. This resulted in the first completely automated IB refolding screening procedure to be developed using a 96-well format. The 96 refolding buffers were obtained using a fractional factorial approach. The screening procedure is potentially applicable to any nonmembrane protein, and was validated with 24 proteins in the framework of two Structural Genomics projects. The tests used for this purpose included the use of quality control methods such as circular dichroism, dynamic light scattering, and crystallogenesis. Out of the 24 proteins, 17 remained soluble in at least one of the 96 refolding buffers, 15 passed large-scale purification tests, and five gave crystals.

To make large-scale association studies a reality, automated high-throughput methods for genotyping with single-nucleotide polymorphisms (SNPs) are needed. We describe PCR conditions that permit the use of the TaqMan or 5′ nuclease allelic discrimination assay for typing large numbers of individuals with any SNP and computational methods that allow genotypes to be assigned automatically. To demonstrate the utility of these methods, we typed >1600 individuals for a G-to-T transversion that results in a glutamate-to-aspartate substitution at position 298 in the endothelial nitric oxide synthase gene, and a G/C polymorphism (newly identified in our laboratory) in intron 8 of the 11–β hydroxylase gene. The genotyping method is accurate—we estimate an error rate of fewer than 1 in 2000 genotypes, rapid—with five 96-well PCR machines, one fluorescent reader, and no automated pipetting, over one thousand genotypes can be generated by one person in one day, and flexible—a new SNP can be tested for association in less than one week. Indeed, large-scale genotyping has been accomplished for 23 other SNPs in 13 different genes using this method. In addition, we identified three “pseudo-SNPs” (WIAF1161, WIAF2566, and WIAF335) that are probably a result of duplication. PMID:11435409

A jet flow singlet oxygen generator (JSOG) capable of handling chlorine flows of nearly 1.5 mol s -1 has been designed, developed, and tested. The generator is designed in a modular configuration taking into consideration the practical aspects of handling highthroughput flows without catastrophic BHP carry over. While for such high flow rates a cross-flow configuration has been reported, the generator utilized in the present study is a counter flow configuration. A near vertical extraction of singlet oxygen is effected at the generator exit, followed by a 90° rotation of the flow forming a novel verti-horizontal COIL scheme. This allows the COIL to be operated with a vertical extraction SOG followed by the horizontal arrangement of subsequent COIL systems such as supersonic nozzle, cavity, supersonic diffuser, etc. This enables a more uniform weight distribution from point of view of mobile and other platform mounted systems, which is highly relevant for large scale systems. The present study discusses the design aspects of the jet singlet oxygen generator along with its test results for various operating ranges. Typically, for the intended design flow rates, the chlorine utilization and singlet oxygen yield have been observed to be ˜94% and ˜64%, respectively.

Motivation: Ultra-high-throughput sequencing produces duplicate and near-duplicate reads, which can consume computational resources in downstream applications. A tool that collapses such reads should reduce storage and assembly complications and costs. Results: We developed Fulcrum to collapse identical and near-identical Illumina and 454 reads (such as those from PCR clones) into single error-corrected sequences; it can process paired-end as well as single-end reads. Fulcrum is customizable and can be deployed on a single machine, a local network or a commercially available MapReduce cluster, and it has been optimized to maximize ease-of-use, cross-platform compatibility and future scalability. Sequence datasets have been collapsed by up to 71%, and the reduced number and improved quality of the resulting sequences allow assemblers to produce longer contigs while using less memory. Availability and implementation: Source code and a tutorial are available at http://pringlelab.stanford.edu/protocols.html under a BSD-like license. Fulcrum was written and tested in Python 2.6, and the single-machine and local-network modes depend on a modified version of the Parallel Python library (provided). Contact: erik.m.lehnert@gmail.com Supplementary information: Supplementary information is available at Bioinformatics online. PMID:22419786

High-throughput sequencing technologies have allowed for the cataloguing of variation in personal human genomes. In this manuscript, we present alu-detect, a tool that combines read-pair and split-read information to detect novel Alus and their precise breakpoints directly from either whole-genome or whole-exome sequencing data while also identifying insertions directly in the vicinity of existing Alus. To set the parameters of our method, we use simulation of a faux reference, which allows us to compute the precision and recall of various parameter settings using real sequencing data. Applying our method to 100 bp paired Illumina data from seven individuals, including two trios, we detected on average 1519 novel Alus per sample. Based on the faux-reference simulation, we estimate that our method has 97% precision and 85% recall. We identify 808 novel Alus not previously described in other studies. We also demonstrate the use of alu-detect to study the local sequence and global location preferences for novel Alu insertions. PMID:23921633

The discovery of new therapeutic options against Trypanosoma cruzi, the causative agent of Chagas disease, stands as a fundamental need. Currently, there are only two drugs available to treat this neglected disease, which represents a major public health problem in Latin America. Both available therapies, benznidazole and nifurtimox, have significant toxic side effects and their efficacy against the life-threatening symptomatic chronic stage of the disease is variable. Thus, there is an urgent need for new, improved anti-T. cruzi drugs. With the objective to reliably accelerate the drug discovery process against Chagas disease, several advances have been made in the last few years. Availability of engineered reporter gene expressing parasites triggered the development of phenotypic in vitro assays suitable for highthroughput screening (HTS) as well as the establishment of new in vivo protocols that allow faster experimental outcomes. Recently, automated high content microscopy approaches have also been used to identify new parasitic inhibitors. These in vitro and in vivo early drug discovery approaches, which hopefully will contribute to bring better anti-T. cruzi drug entities in the near future, are reviewed here.

Molecular shape is important in both crystallisation and supramolecular assembly, yet its role is not completely understood. We present a computationally efficient scheme to describe and classify the molecular shapes in crystals. The method involves rotation invariant description of Hirshfeld surfaces in terms of of spherical harmonic functions. Hirshfeld surfaces represent the boundaries of a molecule in the crystalline environment, and are widely used to visualise and interpret crystalline interactions. The spherical harmonic description of molecular shapes are compared and classified by means of principal component analysis and cluster analysis. When applied to a series of metals, the method results in a clear classification based on their lattice type. When applied to around 300 crystal structures comprising of series of substituted benzenes, naphthalenes and phenylbenzamide it shows the capacity to classify structures based on chemical scaffolds, chemical isosterism, and conformational similarity. The computational efficiency of the method is demonstrated with an application to over 14 thousand crystal structures. Highthroughput screening of molecular shapes and interaction surfaces in the Cambridge Structural Database (CSD) using this method has direct applications in drug discovery, supramolecular chemistry and materials design.

Autophagy is an evolutionally conserved process in cells for cleaning abnormal proteins and organelles in a lysosome dependent manner. Growing studies have shown that defects or induced autophagy contributes to many diseases including aging, neurodegeneration, pathogen infection, and cancer. However, the precise involvement of autophagy in health and disease remains controversial because the theories are built on limited assays and chemical modulators, indicating that the role of autophagy in diseases may require further verification. Many food and drug administration (FDA) approved drugs modulate autophagy signaling, suggesting that modulation of autophagy with pharmacological agonists or antagonists provides a potential therapy for autophagy-related diseases. This suggestion raises an attractive issue on drug discovery for exploring chemical modulators of autophagy. Highthroughput screening (HTS) is becoming a powerful tool for drug discovery that may accelerate screening specific autophagy modulators to clarify the role of autophagy in diseases. Herein, this review lays out current autophagy assays to specifically measure autophagy components such as LC3 (mammalian homologue of yeast Atg8) and Atg4. These assays are feasible or successful for HTS with certain chemical libraries, which might be informative for this intensively growing field as research tools and hopefully developing new drugs for autophagy-related diseases.

In order to detect a biochemical analyte with a mass spectrometer (MS) it is necessary to ionize the analyte of interest. The analyte can be ionized by a number of different mechanisms, however, one common method is electrospray ionization (ESI). Droplets of analyte are sprayed through a highly charged field, the droplets pick up charge, and this is transferred to the analyte. High levels of salt in the assay buffer will potentially steal charge from the analyte and suppress the MS signal. In order to avoid this suppression of signal, salt is often removed from the sample prior to injection into the MS. Traditional ESI MS relies on liquid chromatography (LC) to remove the salt and reduce matrix effects, however, this is a lengthy process. Here we describe the use of RapidFire™ coupled to a triple-quadrupole MS for high-throughput screening. This system uses solid-phase extraction to de-salt samples prior to injection, reducing processing time such that a sample is injected into the MS ~every 10 s.

We describe here a high-throughput assay to support rapid evaluation of drug discovery compounds for possible drug-drug interaction (DDI). Each compound is evaluated for its DDI potential by incubating over a range of eight concentrations and against a panel of six cytochrome P450 (CYP) enzymes: 1A2, 2C8, 2C9, 2C19, 2D6, and 3A4. The method utilizes automated liquid handling for sample preparation, and online solid-phase extraction/tandem mass spectrometry (SPE/MS/MS) for sample analyses. The system is capable of generating two 96-well assay plates in 30 min, and completes the data acquisition and analysis of both plates in about 30 min. Many laboratories that perform the CYP inhibition screening automate only part of the processes leaving a throughput bottleneck within the workflow. The protocols described in this chapter are aimed to streamline the entire process from assay to data acquisition and processing by incorporating automation and utilizing high-precision instrument to maximize throughput and minimize bottleneck.

Following the success of small-molecule high-throughput screening (HTS) in drug discovery, other large-scale screening techniques are currently revolutionizing the biological sciences. Powerful new statistical tools have been developed to analyze the vast amounts of data in DNA chip studies, but have not yet found their way into compound screening. In HTS, characterization of single-point hit lists is often done only in retrospect after the results of confirmation experiments are available. However, for prioritization, for optimal use of resources, for quality control, and for comparison of screens it would be extremely valuable to predict the rates of false positives and false negatives directly from the primary screening results. Making full use of the available information about compounds and controls contained in HTS results and replicated pilot runs, the Z score and from it the p value can be estimated for each measurement. Based on this consideration, we have applied the concept of p-value distribution analysis (PVDA), which was originally developed for gene expression studies, to HTS data. PVDA allowed prediction of all relevant error rates as well as the rate of true inactives, and excellent agreement with confirmation experiments was found.

Identifying chemicals that provide a specific function within a product, yet have minimal impact on the human body or environment, is the goal of most formulation chemists and engineers practicing green chemistry. We present a methodology to identify potential chemical functional substitutes from large libraries of chemicals using machine learning based models. We collect and analyze publicly available information on the function of chemicals in consumer products or industrial processes to identify a suite of harmonized function categories suitable for modeling. We use structural and physicochemical descriptors for these chemicals to build 41 quantitative structure–use relationship (QSUR) models for harmonized function categories using random forest classification. We apply these models to screen a library of nearly 6400 chemicals with available structure information for potential functional substitutes. Using our Functional Use database (FUse), we could identify uses for 3121 chemicals; 4412 predicted functional uses had a probability of 80% or greater. We demonstrate the potential application of the models to high-throughput (HT) screening for “candidate alternatives” by merging the valid functional substitute classifications with hazard metrics developed from HT screening assays for bioactivity. A descriptor set could be obtained for 6356 Tox21 chemicals that have undergone a battery of HT in vitro bioactivity screening assays. By applying QSURs, we wer

High-throughput screening (HTS) has become an indispensable tool for the pharmaceutical industry and for biomedical research. A high degree of automation allows for experiments in the range of a few hundred up to several hundred thousand to be performed in close succession. The basis for such screens are molecular libraries, that is, microtiter plates with solubilized reagents such as siRNAs, shRNAs, miRNA inhibitors or mimics, and sgRNAs, or small compounds, that is, drugs. These reagents are typically condensed to provide enough material for covering several screens. Library plates thus need to be serially diluted before they can be used as assay plates. This process, however, leads to an explosion in the number of plates and samples to be tracked. Here, we present SAVANAH, the first tool to effectively manage molecular screening libraries across dilution series. It conveniently links (connects) sample information from the library to experimental results from the assay plates. All results can be exported to the R statistical environment or piped into HiTSeekR ( http://hitseekr.compbio.sdu.dk ) for comprehensive follow-up analyses. In summary, SAVANAH supports the HTS community in managing and analyzing HTS experiments with an emphasis on serially diluted molecular libraries.

Echogenic particles, such as microbubbles and volatile liquid micro/nano droplets, have shown considerable potential in a variety of clinical diagnostic and therapeutic applications. The accurate prediction of their response to ultrasound excitation is however extremely challenging, and this has hindered the optimisation of techniques such as quantitative ultrasound imaging and targeted drug delivery. Existing characterisation techniques, such as ultra-high speed microscopy provide important insights, but suffer from a number of limitations; most significantly difficulty in obtaining large data sets suitable for statistical analysis and the need to physically constrain the particles, thereby altering their dynamics. Here a microfluidic system is presented that overcomes these challenges to enable the measurement of single echogenic particle response to ultrasound excitation. A co-axial flow focusing device is used to direct a continuous stream of unconstrained particles through the combined focal region of an ultrasound transducer and a laser. Both the optical and acoustic scatter from individual particles are then simultaneously recorded. Calibration of the device and example results for different types of echogenic particle are presented, demonstrating a highthroughput of up to 20 particles per second and the ability to resolve changes in particle radius down to 0.1 μm with an uncertainty of less than 3%.

High-Throughput Screening (HTS) data in its entirety is a valuable raw material for the drug-discovery process. It provides the most compete information about the biological activity of a company's compounds. However, its quantity, complexity and heterogeneity require novel, sophisticated approaches in data analysis. At GeneData, we are developing methods for large-scale, synoptical mining of screening data in a five-step analysis: (1) Quality Assurance: Checking data for experimental artifacts and eliminating low quality data. (2) Biological Profiling: Clustering and ranking of compounds based on their biological activity, taking into account specific characteristics of HTS data. (3) Rule-based Classification: Applying user-defined rules to biological and chemical properties, and providing hypotheses on the biological mode-of-action of compounds. (4) Joint Biological-Chemical Analysis: Associating chemical compound data to HTS data, providing hypotheses for structure- activity relationships. (5) integration with Genomic and Gene Expression Data: Linking into other components of GeneData's bioinformatics platform, and assessing the compounds' modes-of-action, toxicity, and metabolic properties. These analyses address issues that are crucial for a correct interpretation and full exploitation of screening data. They lead to a sound rating of assays and compounds at an early state of the lead-finding process.

Highthroughput process development offers unique approaches to explore complex process design spaces with relatively low material consumption. Batch chromatography is one technique that can be used to screen chromatographic conditions in a 96-well plate. Typical batch chromatography workflows examine variations in buffer conditions or comparison of multiple resins in a given process, as opposed to the assessment of protein loading conditions in combination with other factors. A modification to the batch chromatography paradigm is described here where experimental planning, programming, and a staggered loading approach increase the multivariate space that can be explored with a liquid handling system. The iterative batch chromatography (IBC) approach is described, which treats every well in a 96-well plate as an individual experiment, wherein protein loading conditions can be varied alongside other factors such as wash and elution buffer conditions. As all of these factors are explored in the same experiment, the interactions between them are characterized and the number of follow-up confirmatory experiments is reduced. This in turn improves statistical power and throughput. Two examples of the IBC method are shown and the impact of the load conditions are assessed in combination with the other factors explored.

Recently, machine vision is gaining attention in food science as well as in food industry concerning food quality assessment and monitoring. Into the framework of implementation of Process Analytical Technology (PAT) in the food industry, image processing can be used not only in estimation and even prediction of food quality but also in detection of adulteration. Towards these applications on food science, we present here a novel methodology for automated image analysis of several kinds of food products e.g. meat, vanilla crème and table olives, so as to increase objectivity, data reproducibility, low cost information extraction and faster quality assessment, without human intervention. Image processing's outcome will be propagated to the downstream analysis. The developed multispectral image processing method is based on unsupervised machine learning approach (Gaussian Mixture Models) and a novel unsupervised scheme of spectral band selection for segmentation process optimization. Through the evaluation we prove its efficiency and robustness against the currently available semi-manual software, showing that the developed method is a highthroughput approach appropriate for massive data extraction from food samples.

A major upgrade to the charge exchange recombination spectroscopy system on MAST has recently been implemented. The new system consists of a high-throughput spectrometer coupled to a total of 224 spatial channels, including toroidal and poloidal views of both neutral heating beams on MAST. Radial resolution is {approx}1 cm, comparable to the ion Larmor radius. The toroidal views are configured with 64 channels per beam, while the poloidal views have 32 channels per beam. Background channels for both poloidal and toroidal views are also provided. A large transmission grating is at the heart of the new spectrometer, with high quality single lens reflex lenses providing excellent imaging performance and permitting the full exploitation of the available etendue of the camera sensor. The charge-coupled device camera chosen has four-tap readout at a maximum aggregate speed of 8.8 MHz, and it is capable of reading out the full set of 224 channels in less than 4 ms. The system normally operates at 529 nm, viewing the C{sup 5+} emission line, but can operate at any wavelength in the range of 400-700 nm. Results from operating the system on MAST are shown, including impurity ion temperature and velocity profiles. The system's excellent spatial resolution is ideal for the study of transport barrier phenomena on MAST, an activity which has already been advanced significantly by data from the new diagnostic.

Addressing the neural mechanisms underlying complex learned behaviors requires training animals in well-controlled tasks, an often time-consuming and labor-intensive process that can severely limit the feasibility of such studies. To overcome this constraint, we developed a fully computer-controlled general purpose system for high-throughput training of rodents. By standardizing and automating the implementation of predefined training protocols within the animal’s home-cage our system dramatically reduces the efforts involved in animal training while also removing human errors and biases from the process. We deployed this system to train rats in a variety of sensorimotor tasks, achieving learning rates comparable to existing, but more laborious, methods. By incrementally and systematically increasing the difficulty of the task over weeks of training, rats were able to master motor tasks that, in complexity and structure, resemble ones used in primate studies of motor sequence learning. By enabling fully automated training of rodents in a home-cage setting this low-cost and modular system increases the utility of rodents for studying the neural underpinnings of a variety of complex behaviors. PMID:24349451

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2,060 chemical samples on steroidogenesis via HPLC-MS/MS quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a three stage screening strategy. The first stage established the maximum tolerated concentration (MTC; >70% viability) per sample. The second stage quantified changes in hormone levels at the MTC while the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were pre-stimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2,060 chemical samples evaluated, 524 samples were selected for six-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into five distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A d

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications. PMID:20944202

In the field of drug delivery systems, microparticles made of polymeric matrix appear as an attractive approach. The in vitro release kinetic profile is crucial information when developing new particulate formulations. These data are essential for batch to batch comparison, quality control as well as for anticipation of in vivo behavior to select the best formulation to go further in preclinical investigations. The methods available present common drawbacks such as the time- and compound-consumption that does not fit with formulation screening requirements in early development stages. In this study, a new microscale highthroughput screening (HTS) method has been developed to investigate drug release kinetic from piroxicam-loaded polylactic acid (PLA) and polylactic-co-glycolic acid (PLGA) microparticles. The method is a sample- and separation-based method where separation is performed by filtration using 96-well micro filter plates. 96 experiments can therefore be performed on one plate in one time in a fully automated way and with a very low sample and particle consumption. The influence of different parameters controlling release profiles was also investigated using this technique. The HTS method gave the same release profile than the standard dialysis method. Shaking, particle concentration, and the nature of the release medium were found to be of influence. The HTS method appears as a reliable method to evaluate drug release from particles with smaller standard deviation and less consumption of material.

We present a new next-generation sequencing-based method to identify somatic mutations of lung cancer. It is a comprehensive mutation profiling protocol to detect somatic mutations in 30 genes found frequently in lung adenocarcinoma. The total length of the target regions is 107 kb, and a capture assay was designed to cover 99% of it. This method exhibited about 97% mean coverage at 30× sequencing depth and 42% average specificity when sequencing of more than 3.25 Gb was carried out for the normal sample. We discovered 513 variations from targeted exome sequencing of lung cancer cells, which is 3.9-fold higher than in the normal sample. The variations in cancer cells included previously reported somatic mutations in the COSMIC database, such as variations in TP53, KRAS, and STK11 of sample H-23 and in EGFR of sample H-1650, especially with more than 1,000× coverage. Among the somatic mutations, up to 91% of single nucleotide polymorphisms from the two cancer samples were validated by DNA microarray-based genotyping. Our results demonstrated the feasibility of high-throughput mutation profiling with lung adenocarcinoma samples, and the profiling method can be used as a robust and effective protocol for somatic variant screening. PMID:25031567

This was a poster displayed at the Symposium. Advances on previous highthroughput screening of biomass recalcitrance methods have resulted in improved conversion and replicate precision. Changes in plate reactor metallurgy, improved preparation of control biomass, species-specific pretreatment conditions, and enzymatic hydrolysis parameters have reduced overall coefficients of variation to an average of 6% for sample replicates. These method changes have improved plate-to-plate variation of control biomass recalcitrance and improved confidence in sugar release differences between samples. With smaller errors plant researchers can have a higher degree of assurance more low recalcitrance candidates can be identified. Significant changes in plate reactor, control biomass preparation, pretreatment conditions and enzyme have significantly reduced sample and control replicate variability. Reactor plate metallurgy significantly impacts sugar release aluminum leaching into reaction during pretreatment degrades sugars and inhibits enzyme activity. Removal of starch and extractives significantly decreases control biomass variability. New enzyme formulations give more consistent and higher conversion levels, however required re-optimization for switchgrass. Pretreatment time and temperature (severity) should be adjusted to specific biomass types i.e. woody vs. herbaceous. Desalting of enzyme preps to remove low molecular weight stabilizers and improved conversion levels likely due to water activity impacts on enzyme structure and substrate interactions not attempted here due to need to continually desalt and validate precise enzyme concentration and activity.

We set out to analyze the fundamental biological differences between AAV2 and AAV8 that may contribute to their different performances in vivo. High-throughput protein interaction screens were used to identify binding partners for each serotype. Of the >8,000 proteins probed, 115 and 134 proteins were identified that interact with AAV2 and AAV8, respectively. Notably, 76 of these protein interactions were shared between the two serotypes. CDK2/cyclinA kinase was identified as a binding partner for both serotypes in the screen. Subsequent analysis confirmed direct binding of CDK2/cyclinA by AAV2 and AAV8. Inhibition of CDK2/cyclinA resulted in increased levels of vector transduction. Biophysical study of vector particle stability and genome uncoating demonstrated slightly greater thermostability for AAV8 than for AAV2. Heat-induced genome uncoating occurred at the same temperature as particle degradation, suggesting that these two processes may be intrinsically related for adeno-associated virus (AAV). Together, these analyses provide insight into commonalities and divergences in the biology of functionally distinct hepatotropic AAV serotypes.

Structural health monitoring (SHM) using wireless smart sensors (WSS) has the potential to provide rich information on the state of a structure. However, because of their distributed nature, maintaining highly robust and reliable networks can be challenging. Assessing WSS network communication quality before and after finalizing a deployment is critical to achieve a successful WSS network for SHM purposes. Early studies on WSS network reliability mostly used temporal signal indicators, composed of a smaller number of packets, to assess the network reliability. However, because the WSS networks for SHM purpose often require high data throughput, i.e., a larger number of packets are delivered within the communication, such an approach is not sufficient. Instead, in this study, a model that can assess, probabilistically, the long-term performance of the network is proposed. The proposed model is based on readily-available measured data sets that represent communication quality during high-throughput data transfer. Then, an empirical limit-state function is determined, which is further used to estimate the probability of network communication failure. Monte Carlo simulation is adopted in this paper and applied to a small and a full-bridge wireless networks. By performing the proposed analysis in complex sensor networks, an optimized sensor topology can be achieved.

Highthroughput sequencing (HTS) generates large amounts of high quality sequence data for microbial genomics. The value of HTS for microbial forensics is the speed at which evidence can be collected and the power to characterize microbial-related evidence to solve biocrimes and bioterrorist events. As HTS technologies continue to improve, they provide increasingly powerful sets of tools to support the entire field of microbial forensics. Accurate, credible results allow analysis and interpretation, significantly influencing the course and/or focus of an investigation, and can impact the response of the government to an attack having individual, political, economic or military consequences. Interpretation of the results of microbial forensic analyses relies on understanding the performance and limitations of HTS methods, including analytical processes, assays and data interpretation. The utility of HTS must be defined carefully within established operating conditions and tolerances. Validation is essential in the development and implementation of microbial forensics methods used for formulating investigative leads attribution. HTS strategies vary, requiring guiding principles for HTS system validation. Three initial aspects of HTS, irrespective of chemistry, instrumentation or software are: 1) sample preparation, 2) sequencing, and 3) data analysis. Criteria that should be considered for HTS validation for microbial forensics are presented here. Validation should be defined in terms of specific application and the criteria described here comprise a foundation for investigators to establish, validate and implement HTS as a tool in microbial forensics, enhancing public safety and national security.

New low-cost photoactive hybrid materials based on organic luminescent molecules inserted into hydrotalcite (layered double hydroxides; LDH) were produced, which exploit the high-throughput liquid-assisted grinding (LAG) method. These materials are conceived for applications in dye-sensitized solar cells (DSSCs) as a co-absorbers and in silicon photovoltaic (PV) panels to improve their efficiency as they are able to emit where PV modules show the maximum efficiency. A molecule that shows a large Stokes' shift was designed, synthesized, and intercalated into LDH. Two dyes already used in DSSCs were also intercalated to produce two new nanocomposites. LDH intercalation allows the stability of organic dyes to be improved and their direct use in polymer melt blending. The prepared nanocomposites absorb sunlight from UV to visible and emit from blue to near-IR and thus can be exploited for light-energy management. Finally one nanocomposite was dispersed by melt blending into a poly(methyl methacrylate)-block-poly(n-butyl acrylate) copolymer to obtain a photoactive film.

We introduce an optical platform for rapid, high-throughput screening of exogenous molecules that affect cellular mechanotransduction. Our method initiates mechanotransduction in adherent cells using single laser-microbeam generated microcavitation bubbles without requiring flow chambers or microfluidics. These microcavitation bubbles expose adherent cells to a microtsunami, a transient microscale burst of hydrodynamic shear stress, which stimulates cells over areas approaching 1 mm2. We demonstrate microtsunami-initiated mechanosignalling in primary human endothelial cells. This observed signalling is consistent with G-protein-coupled receptor stimulation, resulting in Ca2+ release by the endoplasmic reticulum. Moreover, we demonstrate the dose-dependent modulation of microtsunami-induced Ca2+ signalling by introducing a known inhibitor to this pathway. The imaging of Ca2+ signalling and its modulation by exogenous molecules demonstrates the capacity to initiate and assess cellular mechanosignalling in real time. We utilize this capability to screen the effects of a set of small molecules on cellular mechanotransduction in 96-well plates using standard imaging cytometry.

Method Taking advantage of the current rapid development in imaging systems and computer vision algorithms, we present HPGA, a high-throughput phenotyping platform for plant growth modeling and functional analysis, which produces better understanding of energy distribution in regards of the balance between growth and defense. HPGA has two components, PAE (Plant Area Estimation) and GMA (Growth Modeling and Analysis). In PAE, by taking the complex leaf overlap problem into consideration, the area of every plant is measured from top-view images in four steps. Given the abundant measurements obtained with PAE, in the second module GMA, a nonlinear growth model is applied to generate growth curves, followed by functional data analysis. Results Experimental results on model plant Arabidopsis thaliana show that, compared to an existing approach, HPGA reduces the error rate of measuring plant area by half. The application of HPGA on the cfq mutant plants under fluctuating light reveals the correlation between low photosynthetic rates and small plant area (compared to wild type), which raises a hypothesis that knocking out cfq changes the sensitivity of the energy distribution under fluctuating light conditions to repress leaf growth. Availability HPGA is available at http://www.msu.edu/~jinchen/HPGA. PMID:24565437

Scientific experiments are producing huge amounts of data, and the size of their datasets and total volume of data continues increasing. These data are then processed by researchers belonging to large scientific collaborations, with the Large Hadron Collider being a good example. The focal point of scientific data centers has shifted from efficiently coping with PetaByte scale storage to deliver quality data processing throughput. The dimensioning of the internal components in HighThroughput Computing (HTC) data centers is of crucial importance to cope with all the activities demanded by the experiments, both the online (data acceptance) and the offline (data processing, simulation and user analysis). This requires a precise setup involving disk and tape storage services, a computing cluster and the internal networking to prevent bottlenecks, overloads and undesired slowness that lead to losses cpu cycles and batch jobs failures. In this paper we point out relevant features for running a successful data storage and processing service in an intensive HTC environment.

Antibiotic resistance genes (ARGs) are present in surface water and often cannot be completely eliminated by drinking water treatment plants (DWTPs). Improper elimination of the ARG-harboring microorganisms contaminates the water supply and would lead to animal and human disease. Therefore, it is of utmost importance to determine the most effective ways by which DWTPs can eliminate ARGs. Here, we tested water samples from two DWTPs and distribution systems and detected the presence of 285 ARGs, 8 transposases, and intI-1 by utilizing high-throughput qPCR. The prevalence of ARGs differed in the two DWTPs, one of which employed conventional water treatments while the other had advanced treatment processes. The relative abundance of ARGs increased significantly after the treatment with biological activated carbon (BAC), raising the number of detected ARGs from 76 to 150. Furthermore, the final chlorination step enhanced the relative abundance of ARGs in the finished water generated from both DWTPs. The total enrichment of ARGs varied from 6.4-to 109.2-fold in tap water compared to finished water, among which beta-lactam resistance genes displayed the highest enrichment. Six transposase genes were detected in tap water samples, with the transposase gene TnpA-04 showing the greatest enrichment (up to 124.9-fold). We observed significant positive correlations between ARGs and mobile genetic elements (MGEs) during the distribution systems, indicating that transposases and intI-1 may contribute to antibiotic resistance in drinking water. To our knowledge, this is the first study to investigate the diversity and abundance of ARGs in drinking water treatment systems utilizing high-throughput qPCR techniques in China.

Mechanisms determining temporal lobe structural asymmetries may be involved in the pathogenesis of schizophrenia. To investigate the temporal lobes in familial schizophrenia, computed tomographic scans were obtained from 51 subjects (seven families). Enlargement of sylvian fissures and temporal lobe sulcal spaces was observed in family members with schizophrenia. The posterior one-third of the sylvian fissure was larger on the left side in subjects with schizophrenia, and larger on the right side in unaffected individuals. This disturbed pattern of posterior sylvian fissure asymmetry suggests that adjacent language regions may be affected in schizophrenia. An intermediate degree of disturbance in subjects who had schizophrenia-related illnesses or were obligate carriers suggests that genetic factors may be important determinants of temporal lobe asymmetries in familial schizophrenia.

Zebrafish have become a widely used model organism to investigate the mechanisms that underlie developmental biology and to study human disease pathology due to their considerable degree of genetic conservation with humans. Chemical genetics entails testing the effect that small molecules have on a biological process and is becoming a popular translational research method to identify therapeutic compounds. Zebrafish are specifically appealing to use for chemical genetics because of their ability to produce large clutches of transparent embryos, which are externally fertilized. Furthermore, zebrafish embryos can be easily drug treated by the simple addition of a compound to the embryo media. Using whole-mount in situ hybridization (WISH), mRNA expression can be clearly visualized within zebrafish embryos. Together, using chemical genetics and WISH, the zebrafish becomes a potent whole organism context in which to determine the cellular and physiological effects of small molecules. Innovative advances have been made in technologies that utilize machine-based screening procedures, however for many labs such options are not accessible or remain cost-prohibitive. The protocol described here explains how to execute a manual high-throughput chemical genetic screen that requires basic resources and can be accomplished by a single individual or small team in an efficient period of time. Thus, this protocol provides a feasible strategy that can be implemented by research groups to perform chemical genetics in zebrafish, which can be useful for gaining fundamental insights into developmental processes, disease mechanisms, and to identify novel compounds and signaling pathways that have medically relevant applications. PMID:25407322

Mutagenesis with ethylmethanesulfonate (EMS) has been the standard for traditional genetic screens, and in recent years has been applied to reversegenetics. However, reverse-genetic strategies require maintaining a viable germline library so that mutations that are discovered can subsequently be recovered. In applying our TILLING (Targeting Induced Local Lesions IN Genomes) method to establish a Drosophila reverse-genetic service (Fly-TILL), we chose to screen the Zuker lines, a large collection of EMS-mutagenized second- and third-chromosome balanced lines that had been established for forward-genetic screening. For the past four years, our Fly-TILL service has screened this collection to provide approximately 150 allelic series of point mutations for the fly community. Our analysis of >2000 point mutations and indels have provided a glimpse into the population dynamics of this valuable genetic resource. We found evidence for selection and differential recovery of mutations, depending on distance from balancer breakpoints. Although this process led to variable mutational densities, we have nevertheless been able to deliver potentially valuable mutations in genes selected by Fly-TILL users. We anticipate that our findings will help guide the future implementation of point-mutation resources for the Drosophila community.

The ultimate goal of structural biology is to understand the structural basis of proteins in cellular processes. In structural biology, the most critical issue is the availability of high-quality samples. “Structural biology-grade” proteins must be generated in the quantity and quality suitable for structure determination using X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. The purification procedures must reproducibly yield homogeneous proteins or their derivatives containing marker atom(s) in milligram quantities. The choice of protein purification and handling procedures plays a critical role in obtaining high-quality protein samples. With structural genomics emphasizing a genome-based approach in understanding protein structure and function, a number of unique structures covering most of the protein folding space have been determined and new technologies with high efficiency have been developed. At the Midwest Center for Structural Genomics (MCSG), we have developed semi-automated protocols for high-throughput parallel protein expression and purification. A protein, expressed as a fusion with a cleavable affinity tag, is purified in two consecutive immobilized metal affinity chromatography (IMAC) steps: (i) the first step is an IMAC coupled with buffer-exchange, or size exclusion chromatography (IMAC-I), followed by the cleavage of the affinity tag using the highly specific Tobacco Etch Virus (TEV) protease; [1] the second step is IMAC and buffer exchange (IMAC-II) to remove the cleaved tag and tagged TEV protease. These protocols have been implemented on multidimensional chromatography workstations and, as we have shown, many proteins can be successfully produced in large-scale. All methods and protocols used for purification, some developed by MCSG, others adopted and integrated into the MCSG purification pipeline and more recently the Center for Structural Genomics of Infectious Diseases (CSGID) purification pipeline, are

This work describes several research projects aimed towards developing new instruments and novel methods for highthroughput chemical and biological analysis. Approaches are taken in two directions. The first direction takes advantage of well-established semiconductor fabrication techniques and applies them to miniaturize instruments that are workhorses in analytical laboratories. Specifically, the first part of this work focused on the development of micropumps and microvalves for controlled fluid delivery. The mechanism of these micropumps and microvalves relies on the electrochemically-induced surface tension change at a mercury/electrolyte interface. A miniaturized flow injection analysis device was integrated and flow injection analyses were demonstrated. In the second part of this work, microfluidic chips were also designed, fabricated, and tested. Separations of two fluorescent dyes were demonstrated in microfabricated channels, based on an open-tubular liquid chromatography (OT LC) or an electrochemically-modulated liquid chromatography (EMLC) format. A reduction in instrument size can potentially increase analysis speed, and allow exceedingly small amounts of sample to be analyzed under diverse separation conditions. The second direction explores the surface enhanced Raman spectroscopy (SERS) as a signal transduction method for immunoassay analysis. It takes advantage of the improved detection sensitivity as a result of surface enhancement on colloidal gold, the narrow width of Raman band, and the stability of Raman scattering signals to distinguish several different species simultaneously without exploiting spatially-separated addresses on a biochip. By labeling gold nanoparticles with different Raman reporters in conjunction with different detection antibodies, a simultaneous detection of a dual-analyte immunoassay was demonstrated. Using this scheme for quantitative analysis was also studied and preliminary dose-response curves from an immunoassay of a

High-throughput screening (HTS) methods for lipases and esterases are generally performed by using synthetic chromogenic substrates (e.g., p-nitrophenyl, resorufin, and umbelliferyl esters) which may be misleading since they are not their natural substrates (e.g., partially or insoluble triglycerides). In previous works, we have shown that soluble nonchromogenic substrates and p-nitrophenol (as a pH indicator) can be used to quantify the hydrolysis and estimate the substrate selectivity of lipases and esterases from several sources. However, in order to implement a spectrophotometric HTS method using partially or insoluble triglycerides, it is necessary to find particular conditions which allow a quantitative detection of the enzymatic activity. In this work, we used Triton X-100, CHAPS, and N-lauroyl sarcosine as emulsifiers, β-cyclodextrin as a fatty acid captor, and two substrate concentrations, 1 mM of tributyrin (TC4) and 5 mM of trioctanoin (TC8), to improve the test conditions. To demonstrate the utility of this method, we screened 12 enzymes (commercial preparations and culture broth extracts) for the hydrolysis of TC4 and TC8, which are both classical substrates for lipases and esterases (for esterases, only TC4 may be hydrolyzed). Subsequent pH-stat experiments were performed to confirm the preference of substrate hydrolysis with the hydrolases tested. We have shown that this method is very useful for screening a high number of lipases (hydrolysis of TC4 and TC8) or esterases (only hydrolysis of TC4) from wild isolates or variants generated by directed evolution using nonchromogenic triglycerides directly in the test.

Imaging cells in a microfluidic chamber with an area scan camera is difficult due to motion blur and data loss during frame readout causing discontinuity of data acquisition as cells move at relatively high speeds through the chamber. We have developed a method to continuously acquire high-resolution images of cells in motion through a microfluidics chamber using a high-speed line scan camera. The sensor acquires images in a line-by-line fashion in order to continuously image moving objects without motion blur. The optical setup comprises an epi-illuminated microscope with a 40X oil immersion, 1.4 NA objective and a 150 mm tube lens focused on a microfluidic channel. Samples containing suspended cells fluorescently stained with 0.01% (w/v) proflavine in saline are introduced into the microfluidics chamber via a syringe pump; illumination is provided by a blue LED (455 nm). Images were taken of samples at the focal plane using an ELiiXA+ 8k/4k monochrome line-scan camera at a line rate of up to 40 kHz. The system's line rate and fluid velocity are tightly controlled to reduce image distortion and are validated using fluorescent microspheres. Image acquisition was controlled via MATLAB's Image Acquisition toolbox. Data sets comprise discrete images of every detectable cell which may be subsequently mined for morphological statistics and definable features by a custom texture analysis algorithm. This high-throughput screening method, comparable to cell counting by flow cytometry, provided efficient examination including counting, classification, and differentiation of saliva, blood, and cultured human cancer cells.

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values and risk screening values. We aim to use computational toxicology and quantitative highthroughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. By coupling qHTS data with adverse outcome pathways (AOPs) we can use ontologies to make predictions about potential hazards and to identify those assays which are sufficient to infer these same hazards. Once those assays are identified, we can use bootstrap natural spline-based metaregression to integrate the evidence across multiple replicates or assays (if a combination of assays are together necessary to be sufficient). In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene (B[k]F) may induce DNA damage and steatosis using qHTS data and two separate AOPs. We also demonstrate how bootstrap natural spline-based metaregression can be used to integrate the data across multiple assay replicates to generate a concentration-response curve. We used this analysis to calculate an internal point of departure of 0.751µM and risk-specific concentrations of 0.378µM for both 1:1,000 and 1:10,000 additive risk for B[k]F induced DNA damage based on the p53 assay. Based on the available evidence, we

For approximately a decade, biophysical methods have been used to validate positive hits selected from high-throughput screening (HTS) campaigns with the goal to verify binding interactions using label-free assays. By applying label-free readouts, screen artifacts created by compound interference and fluorescence are discovered, enabling further characterization of the hits for their target specificity and selectivity. The use of several biophysical methods to extract this type of high-content information is required to prevent the promotion of false positives to the next level of hit validation and to select the best candidates for further chemical optimization. The typical technologies applied in this arena include dynamic light scattering, turbidometry, resonance waveguide, surface plasmon resonance, differential scanning fluorimetry, mass spectrometry, and others. Each technology can provide different types of information to enable the characterization of the binding interaction. Thus, these technologies can be incorporated in a hit-validation strategy not only according to the profile of chemical matter that is desired by the medicinal chemists, but also in a manner that is in agreement with the target protein's amenability to the screening format. Here, we present the results of screening strategies using biophysics with the objective to evaluate the approaches, discuss the advantages and challenges, and summarize the benefits in reference to lead discovery. In summary, the biophysics screens presented here demonstrated various hit rates from a list of ~2000 preselected, IC50-validated hits from HTS (an IC50 is the inhibitor concentration at which 50% inhibition of activity is observed). There are several lessons learned from these biophysical screens, which will be discussed in this article.

Culture-independent studies using next generation sequencing have revolutionized microbial ecology, however, oomycete ecology in soils is severely lagging behind. The aim of this study was to improve and validate standard techniques for using highthroughput sequencing as a tool for studying oomycete communities. The well-known primer sets ITS4, ITS6 and ITS7 were used in the study in a semi-nested PCR approach to target the internal transcribed spacer (ITS) 1 of ribosomal DNA in a next generation sequencing protocol. These primers have been used in similar studies before, but with limited success. We were able to increase the proportion of retrieved oomycete sequences dramatically mainly by increasing the annealing temperature during PCR. The optimized protocol was validated using three mock communities and the method was further evaluated using total DNA from 26 soil samples collected from different agricultural fields in Denmark, and 11 samples from carrot tissue with symptoms of Pythium infection. Sequence data from the Pythium and Phytophthora mock communities showed that our strategy successfully detected all included species. Taxonomic assignments of OTUs from 26 soil sample showed that 95% of the sequences could be assigned to oomycetes including Pythium, Aphanomyces, Peronospora, Saprolegnia and Phytophthora. A high proportion of oomycete reads was consistently present in all 26 soil samples showing the versatility of the strategy. A large diversity of Pythium species including pathogenic and saprophytic species were dominating in cultivated soil. Finally, we analyzed amplicons from carrots with symptoms of cavity spot. This resulted in 94% of the reads belonging to oomycetes with a dominance of species of Pythium that are known to be involved in causing cavity spot, thus demonstrating the usefulness of the method not only in soil DNA but also in a plant DNA background. In conclusion, we demonstrate a successful approach for pyrosequencing of oomycete

High-throughput screening (HTS) experiments provide a valuable resource that reports biological activity of numerous chemical compounds relative to their molecular targets. Building computational models that accurately predict such activity status (active vs. inactive) in specific assays is a challenging task given the large volume of data and frequently small proportion of active compounds relative to the inactive ones. We developed a method, DRAMOTE, to predict activity status of chemical compounds in HTP activity assays. For a class of HTP assays, our method achieves considerably better results than the current state-of-the-art-solutions. We achieved this by modification of a minority oversampling technique. To demonstrate that DRAMOTE is performing better than the other methods, we performed a comprehensive comparison analysis with several other methods and evaluated them on data from 11 PubChem assays through 1,350 experiments that involved approximately 500,000 interactions between chemicals and their target proteins. As an example of potential use, we applied DRAMOTE to develop robust models for predicting FDA approved drugs that have high probability to interact with the thyroid stimulating hormone receptor (TSHR) in humans. Our findings are further partially and indirectly supported by 3D docking results and literature information. The results based on approximately 500,000 interactions suggest that DRAMOTE has performed the best and that it can be used for developing robust virtual screening models. The datasets and implementation of all solutions are available as a MATLAB toolbox online at www.cbrc.kaust.edu.sa/dramote and can be found on Figshare.

Several technologies for characterizing genes and proteins from humans and other organisms use yeast growth or color development as read outs. The yeast two-hybrid assay, for example, detects protein-protein interactions by measuring the growth of yeast on a specific solid medium, or the ability of the yeast to change color when grown on a medium containing a chromogenic substrate. Current systems for analyzing the results of these types of assays rely on subjective and inefficient scoring of growth or color by human experts. Here an image analysis system is described for scoring yeast growth and color development in highthroughput biological assays. The goal is to locate the spots and score them in color images of two types of plates named “X-Gal” and “growth assay” plates, with uniformly placed spots (cell areas) on each plate (both plates in one image). The scoring system relies on color for the X-Gal spots, and texture properties for the growth assay spots. A maximum likelihood projection-based segmentation is developed to automatically locate spots of yeast on each plate. Then color histogram and wavelet texture features are extracted for scoring using an optimal linear transformation. Finally an artificial neural network is used to score the X-Gal and growth assay spots using the extracted features. The performance of the system is evaluated using spots of 60 images. After training the networks using training and validation sets, the system was assessed on the test set. The overall accuracies of 95.4% and 88.2% are achieved respectively for scoring the X-Gal and growth assay spots. PMID:17948730

The design, performance and application of a novel optical system for highthroughput single molecule detection (SMD) configured in a continuous flow format using microfluidics is reported. The system consisted of a microfabricated polymer-based multi-channel fluidic network situated within the optical path of a laser source (λex = 660 nm) with photon transduction accomplished using an electron-multiplying charge coupled device (EMCCD) operated in a frame transfer mode that allowed tracking single molecules as they passed through a large field-of-view (FoV) illumination zone. The microfluidic device consisted of 30 microchannels possessing dimensions of 30 μm (width) × 20 μm (depth) with a 25 mm pitch. Individual molecules were electrokinetically driven through the fluidic network and excited within the wide-field illumination area with the resulting fluorescence collected via an objective and imaged onto the EMCCD camera. The detection system demonstrated sufficient sensitivity to detect single DNA molecules labeled with a fluorescent tag (AlexaFluor 660) identified through their characteristic emission wavelength and the burst of photons produced during their transit through the excitation volume. In its present configuration and fluidic architecture, the sample processing throughput was ∼4.02 × 105 molecules s−1, but could be increased dramatically through the use of narrower channels and a smaller pitch. The system was further evaluated using a single molecule-based fluorescence quenching assay for measuring the population differences between duplexed and single-stranded DNA molecules as a function of temperature for determining the duplex melting temperature, Tm. PMID:19082181

High-throughput phenotyping is a cornerstone of numerous functional genomics projects. In recent years, imaging screens have become increasingly important in understanding gene-phenotype relationships in studies of cells, tissues and whole organisms. Three-dimensional (3D) imaging has risen to prominence in the field of developmental biology for its ability to capture whole embryo morphology and gene expression, as exemplified by the International Mouse Phenotyping Consortium (IMPC). Large volumes of image data are being acquired by multiple institutions around the world that encompass a range of modalities, proprietary software and metadata. To facilitate robust downstream analysis, images and metadata must be standardized to account for these differences. As an open scientific enterprise, making the data readily accessible is essential so that members of biomedical and clinical research communities can study the images for themselves without the need for highly specialized software or technical expertise. In this article, we present a platform of software tools that facilitate the upload, analysis and dissemination of 3D images for the IMPC. Over 750 reconstructions from 80 embryonic lethal and subviable lines have been captured to date, all of which are openly accessible at mousephenotype.org Although designed for the IMPC, all software is available under an open-source licence for others to use and develop further. Ongoing developments aim to increase throughput and improve the analysis and dissemination of image data. Furthermore, we aim to ensure that images are searchable so that users can locate relevant images associated with genes, phenotypes or human diseases of interest.

Abstract High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1,536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently developed quantitative HTS (qHTS) paradigm, which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay. The practical implementation of qHTS for cell-based and biochemical assays across libraries of > 100,000 compounds (e.g., between 700,000 and 2,000,000 sample wells tested) requires maximal efficiency and miniaturization and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully integrated and automated screening system for qHTS at the National Institutes of Health's Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has led to the generation of over 6 million CRCs from > 120 assays in the last 3 years and is a technology that can be widely implemented to increase efficiency of screening and lead generation. PMID:19035846

High-throughput screening (HTS) experiments provide a valuable resource that reports biological activity of numerous chemical compounds relative to their molecular targets. Building computational models that accurately predict such activity status (active vs. inactive) in specific assays is a challenging task given the large volume of data and frequently small proportion of active compounds relative to the inactive ones. We developed a method, DRAMOTE, to predict activity status of chemical compounds in HTP activity assays. For a class of HTP assays, our method achieves considerably better results than the current state-of-the-art-solutions. We achieved this by modification of a minority oversampling technique. To demonstrate that DRAMOTE is performing better than the other methods, we performed a comprehensive comparison analysis with several other methods and evaluated them on data from 11 PubChem assays through 1,350 experiments that involved approximately 500,000 interactions between chemicals and their target proteins. As an example of potential use, we applied DRAMOTE to develop robust models for predicting FDA approved drugs that have high probability to interact with the thyroid stimulating hormone receptor (TSHR) in humans. Our findings are further partially and indirectly supported by 3D docking results and literature information. The results based on approximately 500,000 interactions suggest that DRAMOTE has performed the best and that it can be used for developing robust virtual screening models. The datasets and implementation of all solutions are available as a MATLAB toolbox online at www.cbrc.kaust.edu.sa/dramote and can be found on Figshare. PMID:26658480

Plant organ phenotyping by noninvasive video imaging techniques provides a powerful tool to assess physiological traits, circadian and diurnal rhythms, and biomass production. In particular, growth of individual plant organs is known to exhibit a high plasticity and occurs as a result of the interaction between various endogenous and environmental processes. Thus, any investigation aiming to unravel mechanisms that determine plant or organ growth has to accurately control and document the environmental growth conditions. Here we describe challenges in establishing a recently developed plant root monitoring platform (PlaRoM) specially suited for noninvasive high-throughput plant growth analysis with highest emphasis on the detailed documentation of capture time, as well as light and temperature conditions. Furthermore, we discuss the experimental procedure for measuring root elongation kinetics and key points that must be considered in such measurements. PlaRoM consists of a robotized imaging platform enclosed in a custom designed phytochamber and a root extension profiling software application. This platform has been developed for multi-parallel recordings of root growth phenotypes of up to 50 individual seedlings over several days, with high spatial and temporal resolution. Two Petri dishes are mounted on a vertical sample stage in a custom designed phytochamber that provides exact temperature control. A computer-controlled positioning unit moves these Petri dishes in small increments and enables continuous screening of the surface under a binocular microscope. Detection of the root tip is achieved by applying thresholds on image pixel data and verifying the neighbourhood for each dark pixel. The growth parameters are visualized as position over time or growth rate over time graphs and averaged over consecutive days, light-dark periods and 24 h day periods. This setup enables the investigation of root extension profiles of different genotypes in various growth

Tape-lifting has since its introduction in the early 2000's become a well-established sampling method in forensic DNA analysis. Sampling is quick and straightforward while the following DNA extraction is more challenging due to the "stickiness", rigidity and size of the tape. We have developed, validated and implemented a simple and efficient direct lysis DNA extraction protocol for adhesive tapes that requires limited manual labour. The method uses Chelex beads and is applied with SceneSafe FAST tape. This direct lysis protocol provided higher mean DNA yields than PrepFiler Express BTA on Automate Express, although the differences were not significant when using clothes worn in a controlled fashion as reference material (p=0.13 and p=0.34 for T-shirts and button-down shirts, respectively). Through in-house validation we show that the method is fit-for-purpose for application in casework, as it provides high DNA yields and amplifiability, as well as good reproducibility and DNA extract stability. After implementation in casework, the proportion of extracts with DNA concentrations above 0.01ng/μL increased from 71% to 76%. Apart from providing higher DNA yields compared with the previous method, the introduction of the developed direct lysis protocol also reduced the amount of manual labour by half and doubled the potential throughput for tapes at the laboratory. Generally, simplified manual protocols can serve as a cost-effective alternative to sophisticated automation solutions when the aim is to enable high-throughput DNA extraction of complex crime scene samples.

A simple and automated spot sampling operation mode for a liquid microjunction surface sampling probe/electrospray ionization mass spectrometry (LMJ-SSP/ESI-MS) system is reported. Prior manual and automated spot sampling methods with this probe relied on a careful, relatively slow alignment of the probe and surface distance (<20 microm spacing) to form the probe-to-surface liquid microjunction critical to successful surface sampling. Moreover, sampling multiple spots required retraction of the surface from the probe and a repeat of this careful probe-to-surface distance alignment at the next sampling position. With the method described here, the probe was not positioned as close to the surface, the exact probe-to-surface positioning was found to be less critical (spanning distances from about 100-300 microm), and this distance was not altered during the sampling of an entire array of sample spots. With the probe positioned within the appropriate distance from the surface, the liquid microjunction was formed by letting the liquid from the sampling end of the probe extend out from the probe to the surface. This was accomplished by reducing the self-aspiration liquid flow rate of the probe to a value less than the volume flow rate pumped into the probe. When the self-aspiration rate of the probe was subsequently increased, analytes on the surface that dissolved at the liquid microjunction were aspirated back into the probe with the liquid that created the liquid microjunction and electrosprayed. Presented here are the basics of this new sampling mode, as well as data that illustrate the potential analytical capabilities of the device to conduct high-throughput quantitative analysis.

Combinatorial synthesis methods allow the rapid preparation and processing of large libraries of solid-state materials. The use of these methods, together with the appropriate screening techniques, has recently led to the discovery of materials with promising superconducting, magnetoresistive, luminescent and dielectric properties. Solid-state catalysts, which play an increasingly important role in the chemical and oil industries, represent another class of material amenable to combinatorial synthesis. Yet typically, catalyst discovery still involves inefficient trial-and-error processes, because catalytic activity is inherently difficult to screen. In contrast to superconductivity, magnetoresistivity and dielectric properties, which can be tested by contact probes, or luminescence, which can be observed directly, the assessment of catalytic activity requires the unambiguous detection of a specific product molecule above a small catalyst site on a large library. Screening by in situ infrared thermography and microprobe sampling mass spectrometry, have been suggested, but the first method, while probing activity, provides no information on reaction products, whereas the second is difficult to implement because it requires the transport of minute gas samples from each library site to the detection system. Here I describe the use of laser-induced resonance-enhanced multiphoton ionization for sensitive, selective and high-throughput screening of a library of solid-state catalysts that activate the dehydrogenation of cyclohexane to benzene. I show that benzene, the product molecule, can be selectively photoionized in the vicinity of the catalytic sites, and that the detection of the resultant photoions by an array of microelectrodes provides information on the activity of individual sites. Adaptation of this technique for the screening of other catalytic reactions and larger libraries with smaller site size seems feasible, thus opening up the possibility of exploiting

We implement the use of a graphics processing unit (GPU) in order to achieve real time data processing for high-throughput transmission optical projection tomography imaging. By implementing the GPU we have obtained a 300 fold performance enhancement in comparison to a CPU workstation implementation. This enables to obtain on-the-fly reconstructions enabling for highthroughput imaging. PMID:20052155

Nanomaterial (NM) developmental toxicities are largely unknown. With an extensive variety of NMs available, high-throughput screening methods may be of value for initial characterization of potential hazard. We optimized a zebrafish embryo test as an in vivo high-throughput assay...

Enhanced sensitivity to Wnts is an emerging hallmark of a subset of cancers, defined in part by mutations regulating the abundance of their receptors. Whether these mutations identify a clinical opportunity is an important question. Inhibition of Wnt secretion by blocking an essential post-translational modification, palmitoleation, provides a useful therapeutic intervention. We developed a novel potent, orally available PORCN inhibitor, ETC-1922159 (henceforth called ETC-159) that blocks the secretion and activity of all Wnts. ETC-159 is remarkably effective in treating RSPO-translocation bearing colorectal cancer (CRC) patient-derived xenografts. This is the first example of effective targeted therapy for this subset of CRC. Consistent with a central role of Wnt signaling in regulation of gene expression, inhibition of PORCN in RSPO3-translocated cancers causes a marked remodeling of the transcriptome, with loss of cell cycle, stem cell and proliferation genes, and an increase in differentiation markers. Inhibition of Wnt signaling by PORCN inhibition holds promise as differentiation therapy in genetically defined human cancers. PMID:26257057

Highthroughput genomic assays empower us to study the entire human genome in short time with reasonable cost. Formalin fixed-paraffin-embedded (FFPE) tissue processing remains the most economical approach for longitudinal tissue specimen storage. Therefore, the ability to apply highthroughput genomic applications to FFPE specimens can expand clinical assays and discovery. Many studies have measured the accuracy and repeatability of data generated from FFPE specimens using highthroughput genomic assays. Together, these studies demonstrate feasibility and provide crucial guidance for future studies using FFPE specimens. Here, we summarize the findings of these studies and discuss the limitations of highthroughput data generated from FFPE specimens across several platforms that include microarray, highthroughput sequencing, and NanoString. PMID:28246590

High-throughput quantification of genetically coherent units (GCUs) is essential for deciphering population dynamics and species interactions within a community of microbes. Current techniques for microbial community analyses are, however, not suitable for this kind of high-throughput application. Here, we demonstrate the use of multivariate statistical analysis of complex DNA sequence electropherograms for the effective and accurate estimation of relative genotype abundance in cell samples from mixed microbial populations. The procedure is no more labor-intensive than standard automated DNA sequencing and provides a very effective means of quantitative data acquisition from experimental microbial communities. We present results with the Campylobacter jejuni strain-specific marker gene gltA, as well as the 16S rRNA gene, which is a universal marker across bacterial assemblages. The statistical models computed for these genes are applied to genetic data from two different experimental settings, namely, a chicken infection model and a multispecies anaerobic fermentation model, demonstrating collection of time series data from model bacterial communities. The method presented here is, however, applicable to any experimental scenario where the interest is quantification of GCUs in genetically heterogeneous DNA samples.

Natural history collections have long been used by morphologists, anatomists, and taxonomists to probe the evolutionary process and describe biological diversity. These biological archives also offer great opportunities for genetic research in taxonomy, conservation, systematics, and population biology. They allow assays of past populations, including those of extinct species, giving context to present patterns of genetic variation and direct measures of evolutionary processes. Despite this potential, museum specimens are difficult to work with because natural postmortem processes and preservation methods fragment and damage DNA. These problems have restricted geneticists’ ability to use natural history collections primarily by limiting how much of the genome can be surveyed. Recent advances in DNA sequencing technology, however, have radically changed this, making truly genomic studies from museum specimens possible. We review the opportunities and drawbacks of the use of museum specimens, and suggest how to best execute projects when incorporating such samples. Several high-throughput (HT) sequencing methodologies, including whole genome shotgun sequencing, sequence capture, and restriction digests (demonstrated here), can be used with archived biomaterials. PMID:25532801

Natural history collections have long been used by morphologists, anatomists, and taxonomists to probe the evolutionary process and describe biological diversity. These biological archives also offer great opportunities for genetic research in taxonomy, conservation, systematics, and population biology. They allow assays of past populations, including those of extinct species, giving context to present patterns of genetic variation and direct measures of evolutionary processes. Despite this potential, museum specimens are difficult to work with because natural postmortem processes and preservation methods fragment and damage DNA. These problems have restricted geneticists' ability to use natural history collections primarily by limiting how much of the genome can be surveyed. Recent advances in DNA sequencing technology, however, have radically changed this, making truly genomic studies from museum specimens possible. We review the opportunities and drawbacks of the use of museum specimens, and suggest how to best execute projects when incorporating such samples. Several high-throughput (HT) sequencing methodologies, including whole genome shotgun sequencing, sequence capture, and restriction digests (demonstrated here), can be used with archived biomaterials.

A number of species of microalgae and cyanobacteria photosynthetically produce H2 gas by coupling water oxidation with the reduction of protons to molecular hydrogen, generating renewable energy from sunlight and water. Photosynthetic H2 production, however, is transitory, and there is considerable interest in increasing and extending it for commercial applications. Here we report a Petri-plate version of our previous, microplate-based assay that detects photosynthetic H2 production by algae. The assay consists of an agar overlay of H2-sensing Rhodobacter capsulatus bacteria carrying a green fluorescent protein that responds to H2 produced by single algal colonies in the bottom agar layer. The assay distinguishes between algal strains that photoproduce H2 at different levels under high light intensities, and it does so in a simple, inexpensive, and high-throughput manner. The assay will be useful for screening both natural populations and mutant libraries for strains having increased H2 production, and useful for identifying various genetic factors that physiologically or genetically alter algal hydrogen production.

Leaf senescence is influenced by its life history, comprising a series of developmental and physiological experiences. Exploration of the biological principles underlying leaf lifespan and senescence requires a schema to trace leaf phenotypes, based on the interaction of genetic and environmental factors. We developed a new approach and concept that will facilitate systemic biological understanding of leaf lifespan and senescence, utilizing the phenome high-throughput investigator (PHI) with a single-leaf-basis phenotyping platform. Our pilot tests showed empirical evidence for the feasibility of PHI for quantitative measurement of leaf senescence responses and improved performance in order to dissect the progression of senescence triggered by different senescence-inducing factors as well as genetic mutations. Such an establishment enables new perspectives to be proposed, which will be challenged for enhancing our fundamental understanding on the complex process of leaf senescence. We further envision that integration of phenomic data with other multi-omics data obtained from transcriptomic, proteomic, and metabolic studies will enable us to address the underlying principles of senescence, passing through different layers of information from molecule to organism. PMID:28280501

The common occurrence of toxic cyanobacteria causes problems for health of animals and human beings. More research and good monitoring systems are needed to protect water users. It is important to have rapid, reliable and accurate analysis i.e. highthroughput methods to identify the toxins as well as toxin producers in the environment. Excellent methods, such as ELISA already exist to analyse cyanobacterial hepatotoxins and saxitoxins, and PPIA for microcystins and nodularins. The LC/MS method can be fast in identifying the toxicants in the samples. Further development of this area should resolve the problems with sampling and sample preparation, which still are the bottlenecks of rapid analyses. In addition, the availability of reliable reference materials and standards should be resolved. Molecular detection methods are now routine in clinical and criminal laboratories and may also become important in environmental diagnostics. One prerequisite for the development of molecular analysis is that pure cultures of the producer organisms are available for identification of the biosynthetic genes responsible for toxin production and for proper testing of the diagnostic methods. Good methods are already available for the microcystin and nodularin-producing cyanobacteria such as conventional PCR, quantitative real-time PCR and microarrays/DNA chips. The DNA-chip technology offers an attractive monitoring system for toxic and non-toxic cyanobacteria. Only with these new technologies (PCR + DNA-chips) will we be able to study toxic cyanobacteria populations in situ and the effects of environmental factors on the occurrence and proliferation of especially toxic cyanobacteria. This is likely to yield important information for mitigation purposes. Further development of these methods should include all cyanobacterial biodiversity, including all toxin producers and primers/probes to detect producers of neurotoxins, cylindrospermopsins etc. (genes are unknown). The on

In recent years, the advantages of using small invertebrate animals as model systems for human disease have become increasingly apparent and have resulted in three Nobel Prizes in medicine or chemistry during the last six years for studies conducted on the nematode Caenorhabditis elegans (C. elegans). The availability of a wide array of species-specific genetic techniques, along with the transparency of the worm and its ability to grow in minute volumes make C. elegans an extremely powerful model organism. We present a suite of technologies for complex high-throughput whole-animal genetic and drug screens. We demonstrate a high-speed microfluidic sorter that can isolate and immobilize C. elegans in a well-defined geometry, an integrated chip containing individually addressable screening chambers for incubation and exposure of individual animals to biochemical compounds, and a device for delivery of compound libraries in standard multiwell plates to microfluidic devices. The immobilization stability obtained by these devices is comparable to that of chemical anesthesia and the immobilization process does not affect lifespan, progeny production, or other aspects of animal health. The high-stability enables the use of a variety of key optical techniques. We use this to demonstrate femtosecond-laser nanosurgery and three-dimensional multiphoton microscopy. Used alone or in various combinations these devices facilitate a variety of high-throughput assays using whole animals, including mutagenesis and RNAi and drug screens at subcellular resolution, as well as high-throughput high-precision manipulations such as femtosecond-laser nanosurgery for large-scale in vivo neural degeneration and regeneration studies.

Background Microsatellites (MSs) are DNA markers with high analytical power, which are widely used in population genetics, genetic mapping, and forensic studies. Currently available software solutions for high-throughput MS design (i) have shortcomings in detecting and distinguishing imperfect and perfect MSs, (ii) lack often necessary interactive design steps, and (iii) do not allow for the development of primers for multiplex amplifications. We present a set of new tools implemented as extensions to the STADEN package, which provides the backbone functionality for flexible sequence analysis workflows. The possibility to assemble overlapping reads into unique contigs (provided by the base functionality of the STADEN package) is important to avoid developing redundant markers, a feature missing from most other similar tools. Results Our extensions to the STADEN package provide the following functionality to facilitate microsatellite (and also minisatellite) marker design: The new modules (i) integrate the state-of-the-art tandem repeat detection and analysis software PHOBOS into workflows, (ii) provide two separate repeat detection steps – with different search criteria – one for masking repetitive regions during assembly of sequencing reads and the other for designing repeat-flanking primers for MS candidate loci, (iii) incorporate the widely used primer design program PRIMER3 into STADEN workflows, enabling the interactive design and visualization of flanking primers for microsatellites, and (iv) provide the functionality to find optimal locus- and primer pair combinations for multiplex primer design. Furthermore, our extensions include a module for storing analysis results in an SQLite database, providing a transparent solution for data access from within as well as from outside of the STADEN Package. Conclusion The STADEN package is enhanced by our modules into a highly flexible, high-throughput, interactive tool for conventional and multiplex

Programmed cell death is a ubiquitous process in metazoan development. Apoptosis, one cell death form, has been studied extensively. However, mutations inactivating key mammalian apoptosis regulators do not block most developmental cell culling, suggesting that other cell death pathways are likely important. Recent work in the nematode Caenorhabditis elegans identified a non-apoptotic cell death form mediating the demise of the male-specific linker cell. This cell death process (LCD, linker cell-type death) is morphologically conserved, and its molecular effectors also mediate axon degeneration in mammals and Drosophila. To develop reagents to manipulate LCD, we established a simple high-throughput screening protocol for interrogating the effects of small molecules on C. elegans linker cell death in vivo. From 23,797 compounds assayed, 11 reproducibly block linker cell death onset. Of these, five induce animal lethality, and six promote a reversible developmental delay. These results provide proof-of principle validation of our screening protocol, demonstrate that developmental progression is required for linker cell death, and suggest that larger scale screens may identify LCD-specific small-molecule regulators that target the LCD execution machinery. PMID:27716809

Mutations in chromatin-modifying proteins and transcription factors are commonly associated with a wide variety of cancers. Through gain- or loss-of-function, these mutations may result in characteristic alterations of accessible chromatin, indicative of shifts in the landscape of regulatory elements genome-wide. The identification of compounds that reverse a specific chromatin signature could lead to chemical probes or potential therapies. To explore whether chromatin accessibility could serve as a platform for small molecule screening, we adapted formaldehyde-assisted isolation of regulatory elements (FAIRE), a chemical method to enrich for nucleosome-depleted genomic regions, as a high-throughput, automated assay. After demonstrating the validity and robustness of this approach, we applied this method to screen an epigenetically targeted small molecule library by evaluating regions of aberrant nucleosome depletion mediated by EWSR1-FLI1, the chimeric transcription factor critical for the bone and soft tissue tumor Ewing sarcoma. As a class, histone deacetylase inhibitors were greatly overrepresented among active compounds. These compounds resulted in diminished accessibility at targeted sites by disrupting transcription of EWSR1-FLI1. Capitalizing on precise differences in chromatin accessibility for drug discovery efforts offers significant advantages because it does not depend on the a priori selection of a single molecular target and may detect novel biologically relevant pathways. PMID:26929321

Background High-throughput real-time quantitative reverse transcriptase polymerase chain reaction (qPCR) is a widely used technique in experiments where expression patterns of genes are to be profiled. Current stage technology allows the acquisition of profiles for a moderate number of genes (50 to a few thousand), and this number continues to grow. The use of appropriate normalization algorithms for qPCR-based data is therefore a highly important aspect of the data preprocessing pipeline. Results We present and evaluate two data-driven normalization methods that directly correct for technical variation and represent robust alternatives to standard housekeeping gene-based approaches. We evaluated the performance of these methods against a single gene housekeeping gene method and our results suggest that quantile normalization performs best. These methods are implemented in freely-available software as an R package qpcrNorm distributed through the Bioconductor project. Conclusion The utility of the approaches that we describe can be demonstrated most clearly in situations where standard housekeeping genes are regulated by some experimental condition. For large qPCR-based data sets, our approaches represent robust, data-driven strategies for normalization. PMID:19374774

Virtual and high-throughput screens (HTS) should have complementary strengths and weaknesses, but studies that prospectively and comprehensively compare them are rare. We undertook a parallel docking and HTS screen of 197861 compounds against cruzain, a thiol protease target for Chagas disease, looking for reversible, competitive inhibitors. On workup, 99% of the hits were eliminated as false positives, yielding 146 well-behaved, competitive ligands. These fell into five chemotypes: two were prioritized by scoring among the top 0.1% of the docking-ranked library, two were prioritized by behavior in the HTS and by clustering, and one chemotype was prioritized by both approaches. Determination of an inhibitor/cruzain crystal structure and comparison of the high-scoring docking hits to experiment illuminated the origins of docking false-negatives and false-positives. Prioritizing molecules that are both predicted by docking and are HTS-active yields well-behaved molecules, relatively unobscured by the false-positives to which both techniques are individually prone. PMID:20540517

Salt-induced protein precipitation and hydrophobic interaction chromatography (HIC) are two widely used methods for protein purification. In this study, salt effects in protein precipitation and HIC were investigated for a broad combination of proteins, salts and HIC resins. Interrelation between the critical thermodynamic salting out parameters in both techniques was equally investigated. Protein precipitation data were obtained by a high-throughput technique employing 96-well microtitre plates and robotic liquid handling technology. For the same protein-salt combinations, isocratic HIC experiments were performed using two or three different commercially available stationary phases-Phenyl Sepharose low sub, Butyl Sepharose and Resource Phenyl. In general, similar salt effects and deviations from the lyotropic series were observed in both separation methods, for example, the reverse Hofmeister effect reported for lysozyme below its isoelectric point and at low salt concentrations. The salting out constant could be expressed in terms of the preferential interaction parameter in protein precipitation, showing that the former is, in effect, the net result of preferential interaction of a protein with water molecules and salt ions in its vicinity. However, no general quantitative interrelation was found between salting out parameters or the number of released water molecules in protein precipitation and HIC. In other words, protein solubility and HIC retention factor could not be quantitatively interrelated, although for some proteins, regular trends were observed across the different resins and salt types.

Palmitoylation is a widespread, reversible lipid modification that has been implicated in regulating a variety of cellular processes. Approximately one thousand proteins are annotated as being palmitoylated, and for some of these, including several oncogenes of the Ras and Src families, palmitoylation is indispensable for protein function. Despite this wealth of disease-relevant targets, there are currently few effective pharmacological tools to interfere with protein palmitoylation. One reason for this lack of development is the dearth of assays to efficiently screen for small molecular inhibitors of palmitoylation. To address this shortcoming, we have developed a robust, high-throughput compatible, click chemistry-based approach to identify small molecules that interfere with the palmitoylation of Ras, a high value therapeutic target that is mutated in up to a third of human cancers. This assay design shows excellent performance in 384-well format and is sensitive to known, non-specific palmitoylation inhibitors. Further, we demonstrate an ideal counter-screening strategy, which relies on a target peptide from an unrelated protein, the Src-family kinase Fyn. The screening approach described here provides an integrated platform to identify specific modulators of palmitoylated proteins, demonstrated here for Ras and Fyn, but potentially applicable to pharmaceutical targets involved in a variety of human diseases. PMID:28112226

Sex determination in animals is amazingly plastic. Vertebrates display contrasting strategies ranging from complete genetic control of sex (genotypic sex determination) to environmentally determined sex (for example, temperature-dependent sex determination). Phylogenetic analyses suggest frequent evolutionary transitions between genotypic and temperature-dependent sex determination in environmentally sensitive lineages, including reptiles. These transitions are thought to involve a genotypic system becoming sensitive to temperature, with sex determined by gene-environment interactions. Most mechanistic models of transitions invoke a role for sex reversal. Sex reversal has not yet been demonstrated in nature for any amniote, although it occurs in fish and rarely in amphibians. Here we make the first report of reptile sex reversal in the wild, in the Australian bearded dragon (Pogona vitticeps), and use sex-reversed animals to experimentally induce a rapid transition from genotypic to temperature-dependent sex determination. Controlled mating of normal males to sex-reversed females produces viable and fertile offspring whose phenotypic sex is determined solely by temperature (temperature-dependent sex determination). The W sex chromosome is eliminated from this lineage in the first generation. The instantaneous creation of a lineage of ZZ temperature-sensitive animals reveals a novel, climate-induced pathway for the rapid transition between genetic and temperature-dependent sex determination, and adds to concern about adaptation to rapid global climate change.

Automation has long been a resource for high-throughput screening at Bristol-Myers Squibb. However, with growing deck sizes and decreasing time lines, a new generation of more robust, supportable automated systems was necessary for accomplishing high-throughput screening goals. Implementation of this new generation of automated systems required numerous decisions concerning hardware, software and the value of in-house automation expertise. This project has resulted in fast, flexible, industrialized automation systems with a strong in-house support structure that we believe meets our current high-throughput screening requirements and will continue to meet them well into the future. PMID:18924614

Leaves are the plant’s solar panel and food factory, and leaf traits are always key issues to investigate in plant research. Traditional methods for leaf trait measurement are time-consuming. In this work, an engineering prototype has been established for high-throughput leaf scoring (HLS) of a large number of Oryza sativa accessions. The mean absolute per cent of errors in traditional measurements versus HLS were below 5% for leaf number, area, shape, and colour. Moreover, HLS can measure up to 30 leaves per minute. To demonstrate the usefulness of HLS in dissecting the genetic bases of leaf traits, a genome-wide association study (GWAS) was performed for 29 leaf traits related to leaf size, shape, and colour at three growth stages using HLS on a panel of 533 rice accessions. Nine associated loci contained known leaf-related genes, such as Nal1 for controlling the leaf width. In addition, a total of 73, 123, and 177 new loci were detected for traits associated with leaf size, colour, and shape, respectively. In summary, after evaluating the performance with a large number of rice accessions, the combination of GWAS and high-throughput leaf phenotyping (HLS) has proven a valuable strategy to identify the genetic loci controlling rice leaf traits. PMID:25796084

Leaves are the plant's solar panel and food factory, and leaf traits are always key issues to investigate in plant research. Traditional methods for leaf trait measurement are time-consuming. In this work, an engineering prototype has been established for high-throughput leaf scoring (HLS) of a large number of Oryza sativa accessions. The mean absolute per cent of errors in traditional measurements versus HLS were below 5% for leaf number, area, shape, and colour. Moreover, HLS can measure up to 30 leaves per minute. To demonstrate the usefulness of HLS in dissecting the genetic bases of leaf traits, a genome-wide association study (GWAS) was performed for 29 leaf traits related to leaf size, shape, and colour at three growth stages using HLS on a panel of 533 rice accessions. Nine associated loci contained known leaf-related genes, such as Nal1 for controlling the leaf width. In addition, a total of 73, 123, and 177 new loci were detected for traits associated with leaf size, colour, and shape, respectively. In summary, after evaluating the performance with a large number of rice accessions, the combination of GWAS and high-throughput leaf phenotyping (HLS) has proven a valuable strategy to identify the genetic loci controlling rice leaf traits.

National Center on Educational Media and Materials for the Handicapped, Columbus, OH.

Selected from the National Instructional Materials Information System (NIMIS)--a computer based on-line interactive retrieval system on special education materials--the bibliography covers nine materials for remediating reversals in handicapped students at the early childhood and elementary levels. Entries are presented in order of NIMIS accession…

Background Genetic maps constitute the basis of breeding programs for many agricultural organisms. The creation of these maps is dependent on marker discovery. Melon, among other crops, is still lagging in genomic resources, limiting the ability to discover new markers in a high-throughput fashion. One of the methods used to search for molecular markers is DNA hybridization to microarrays. Microarray hybridization of DNA from different accessions can reveal differences between them--single-feature polymorphisms (SFPs). These SFPs can be used as markers for breeding purposes, or they can be converted to conventional markers by sequencing. This method has been utilized in a few different plants to discover genetic variation, using Affymetrix arrays that exist for only a few organisms. We applied this approach with some modifications for marker discovery in melon. Results Using a custom-designed oligonucleotide microarray based on a partial EST collection of melon, we discovered 6184 putative SFPs between the parents of our mapping population. Validation by sequencing of 245 SFPs from the two parents showed a sensitivity of around 79%. Most SFPs (81%) contained single-nucleotide polymorphisms. Testing the SFPs on another mapping population of melon confirmed that many of them are conserved. Conclusion Thousands of new SFPs that can be used for genetic mapping and molecular-assisted breeding in melon were discovered using a custom-designed oligo microarray. A portion of these SFPs are conserved and can be used in different breeding populations. Although improvement of the discovery rate is still needed, this approach is applicable to many agricultural systems with limited genomic resources. PMID:20426811

Copy-choice recombination efficiently reshuffles genetic markers in retroviruses. In vivo, the folding of the genomic RNA is controlled by the nucleocapsid protein (NC). We show that binding of NC onto the acceptor RNA molecule is sufficient to enhance recombination, providing evidence for a mechanism where the structure of the acceptor template determines the template switch. NC as well as another RNA chaperone (StpA) converts recombination into a widespread process no longer restricted to rare hot spots, an effect maximized when both the NC and the reverse transcriptase come from HIV-1. These data suggest that RNA chaperones confer a higher genetic flexibility to retroviruses. PMID:10829081

We have developed a microplate reader that records a complete high-quality fluorescence emission spectrum on a well-by-well basis under true high-throughput screening (HTS) conditions. The read time for an entire 384-well plate is less than 3 min. This instrument is particularly well suited for assays based on fluorescence resonance energy transfer (FRET). Intramolecular protein biosensors with genetically encoded green fluorescent protein (GFP) donor and red fluorescent protein (RFP) acceptor tags at positions sensitive to structural changes were stably expressed and studied in living HEK cells. Accurate quantitation of FRET was achieved by decomposing each observed spectrum into a linear combination of four component (basis) spectra (GFP emission, RFP emission, water Raman, and cell autofluorescence). Excitation and detection are both conducted from the top, allowing for thermoelectric control of the sample temperature from below. This spectral unmixing plate reader (SUPR) delivers an unprecedented combination of speed, precision, and accuracy for studying ensemble-averaged FRET in living cells. It complements our previously reported fluorescence lifetime plate reader, which offers the feature of resolving multiple FRET populations within the ensemble. The combination of these two direct waveform-recording technologies greatly enhances the precision and information content for HTS in drug discovery.

Microsatellites (or SSRs: simple sequence repeats) are among the most frequently used DNA markers in many areas of research. The use of microsatellite markers is limited by the difficulties involved in their de novo isolation from species for which no genomic resources are available. We describe here a high-throughput method for isolating microsatellite markers based on coupling multiplex microsatellite enrichment and next-generation sequencing on 454 GS-FLX Titanium platforms. The procedure was calibrated on a model species (Apis mellifera) and validated on 13 other species from various taxonomic groups (animals, plants and fungi), including taxa for which severe difficulties were previously encountered using traditional methods. We obtained from 11,497 to 34,483 sequences depending on the species and the number of detected microsatellite loci ranged from 199 to 5791. We thus demonstrated that this procedure can be readily and successfully applied to a large variety of taxonomic groups, at much lower cost than would have been possible with traditional protocols. This method is expected to speed up the acquisition of high-quality genetic markers for nonmodel organisms.

Over the past decade, bacterial genome sequences have revealed an immense reservoir of biosynthetic gene clusters, sets of contiguous genes that have the potential to produce drugs or drug-like molecules. However, the majority of these gene clusters appear to be inactive for unknown reasons prompting terms such as “cryptic” or “silent” to describe them. Because natural products have been a major source of therapeutic molecules, methods that rationally activate these silent clusters would have a profound impact on drug discovery. Herein, a new strategy is outlined for awakening silent gene clusters using small molecule elicitors. In this method, a genetic reporter construct affords a facile read-out for activation of the silent cluster of interest, while high-throughput screening of small molecule libraries provides potential inducers. This approach was applied to two cryptic gene clusters in the pathogenic model Burkholderia thailandensis. The results not only demonstrate a prominent activation of these two clusters, but also reveal that the majority of elicitors are themselves antibiotics, most in common clinical use. Antibiotics, which kill B. thailandensis at high concentrations, act as inducers of secondary metabolism at low concentrations. One of these antibiotics, trimethoprim, served as a global activator of secondary metabolism by inducing at least five biosynthetic pathways. Further application of this strategy promises to uncover the regulatory networks that activate silent gene clusters while at the same time providing access to the vast array of cryptic molecules found in bacteria. PMID:24808135

Characterizing the errors generated by common high-throughput sequencing platforms and telling true genetic variation from technical artefacts are two interdependent steps, essential to many analyses such as single nucleotide variant calling, haplotype inference, sequence assembly and evolutionary studies. Both random and systematic errors can show a specific occurrence profile for each of the six prominent sequencing platforms surveyed here: 454 pyrosequencing, Complete Genomics DNA nanoball sequencing, Illumina sequencing by synthesis, Ion Torrent semiconductor sequencing, Pacific Biosciences single-molecule real-time sequencing and Oxford Nanopore sequencing. There is a large variety of programs available for error removal in sequencing read data, which differ in the error models and statistical techniques they use, the features of the data they analyse, the parameters they determine from them and the data structures and algorithms they use. We highlight the assumptions they make and for which data types these hold, providing guidance which tools to consider for benchmarking with regard to the data properties. While no benchmarking results are included here, such specific benchmarks would greatly inform tool choices and future software development. The development of stand-alone error correctors, as well as single nucleotide variant and haplotype callers, could also benefit from using more of the knowledge about error profiles and from (re)combining ideas from the existing approaches presented here.

Several pharmacogenetic studies are focused on the investigation of the relation between the efficacy of various antipsychotic agents (e.g., clozapine) and the genetic profile of the patient with an emphasis on genes that code for neurotransmitter receptors such as histamine, serotonin, and adrenergic receptors. We report a high-throughput method for genotyping of single nucleotide polymorphisms (SNPs) within the genes of histamine H2 receptor (HRH2), serotonin receptor (HTR2A1 and HTR2A2), and beta(3) adrenergic receptor (ADRB3). The method combines the high specificity of allele discrimination by oligonucleotide ligation reaction (OLR) and the superior sensitivity and simplicity of chemiluminometric detection in a microtiter well assay configuration. The genomic region that spans the locus of interest is first amplified by polymerase chain reaction (PCR). Subsequently, an oligonucleotide ligation reaction is performed using a biotinylated common probe and two allele-specific probes that are labeled at the 3' end with digoxigenin and fluorescein. The ligation products are immobilized in polystyrene wells via biotin-streptavidin interaction, and the hybrids are denatured. Detection is accomplished by the addition of alkaline phosphatase-conjugated anti-digoxigenin or anti-fluorescein antibodies in combination with a chemiluminogenic substrate. The ratio of the luminescence signals obtained from digoxigenin and fluorescein indicates the genotype of the sample. The method was applied successfully to the genotyping of 23 blood samples for all four SNPs. The results were in concordance with both PCR-restriction fragment length polymorphism analysis and sequencing.

Future improvement of woody biomass crops such as willow and poplar relies on our ability to select for metabolic traits that sequester more atmospheric carbon into biomass, or into useful products to replace petrochemical streams. We describe the development of metabotyping screens for willow, using combined 1D 1H-NMR-MS. A protocol was developed to overcome 1D 1H-NMR spectral alignment problems caused by variable pH and peak broadening arising from high organic acid levels and metal cations. The outcome was a robust method to allow direct statistical comparison of profiles arising from source (leaf) and sink (stem) tissues allowing data to be normalised to a constant weight of the soluble metabolome. We also describe the analysis of two willow biomass varieties, demonstrating how fingerprints from 1D 1H-NMR-MS vary from the top to the bottom of the plant. Automated extraction of quantitative data of 56 primary and secondary metabolites from 1D 1H-NMR spectra was realised by the construction and application of a Salix metabolite spectral library using the Chenomx software suite. The optimised metabotyping screen in conjunction with automated quantitation will enable high-throughput screening of genetic collections. It also provides genotype and tissue specific data for future modelling of carbon flow in metabolic networks. PMID:25353313

Transposable elements (TEs) represent a major fraction of plant genomes and drive their evolution. An improved understanding of genome evolution requires the dynamics of a large number of TE families to be considered. We put forward an approach bypassing the required step of a complete reference genome to assess the evolutionary trajectories of high copy number TE families from genome snapshot with high-throughput sequencing. Low coverage sequencing of the complex genomes of Aegilops cylindrica and Ae. geniculata using 454 identified more than 70% of the sequences as known TEs, mainly long terminal repeat (LTR) retrotransposons. Comparing the abundance of reads as well as patterns of sequence diversity and divergence within and among genomes assessed the dynamics of 44 major LTR retrotransposon families of the 165 identified. In particular, molecular population genetics on individual TE copies distinguished recently active from quiescent families and highlighted different evolutionary trajectories of retrotransposons among related species. This work presents a suite of tools suitable for current sequencing data, allowing to address the genome-wide evolutionary dynamics of TEs at the family level and advancing our understanding of the evolution of nonmodel genomes.

Mitochondrial DNA (mtDNA) profiles can be classified into phylogenetic clusters (haplogroups), which is of great relevance for evolutionary, forensic and medical genetics. With the extensive growth of the underlying phylogenetic tree summarizing the published mtDNA sequences, the manual process of haplogroup classification would be too time-consuming. The previously published classification tool HaploGrep provided an automatic way to address this issue. Here, we present the completely updated version HaploGrep 2 offering several advanced features, including a generic rule-based system for immediate quality control (QC). This allows detecting artificial recombinants and missing variants as well as annotating rare and phantom mutations. Furthermore, the handling of high-throughput data in form of VCF files is now directly supported. For data output, several graphical reports are generated in real time, such as a multiple sequence alignment format, a VCF format and extended haplogroup QC reports, all viewable directly within the application. In addition, HaploGrep 2 generates a publication-ready phylogenetic tree of all input samples encoded relative to the revised Cambridge Reference Sequence. Finally, new distance measures and optimizations of the algorithm increase accuracy and speed-up the application. HaploGrep 2 can be accessed freely and without any registration at http://haplogrep.uibk.ac.at. PMID:27084951

Translation of novel therapies from bench to bedside is hampered by profound disparities between animal and human genetics and physiology. The ability to test for efficacy and cardiotoxicity in a clinically relevant human model system would enable more rapid therapy development. We have developed a preclinical platform for validation of new therapies in human heart tissue using organotypic slices isolated from donor and end-stage failing hearts. A major advantage of the slices when compared with human iPS-derived cardiomyocytes is that native tissue architecture and extracellular matrix are preserved, thereby allowing investigation of multi-cellular physiology in normal or diseased myocardium. To validate this model, we used optical mapping of transmembrane potential and calcium transients. We found that normal human electrophysiology is preserved in slice preparations when compared with intact hearts, including slices obtained from the region of the sinus node. Physiology is maintained in slices during culture, enabling testing the acute and chronic effects of pharmacological, gene, cell, optogenetic, device, and other therapies. This methodology offers a powerful high-throughput platform for assessing the physiological response of the human heart to disease and novel putative therapies. PMID:27356882

Background Analysis of HighThroughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data. Result WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery. Conclusion This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at . PMID:16423281

Drosophila melanogaster is widely used as a model system for development and disease. Due to the homology between Drosophila and human genes, as well as the tractable genetics of the fly, its use as a model for neurologic disorders, in particular, has been rising. Locomotive impairment is a commonly used diagnostic for screening and characterization of these models, yet a fast, sensitive and model-free method to compare behavior is lacking. Here, we present a highthroughput method to quantify the crawling behavior of larvae. We use the mean squared displacement as well as the direction autocorrelation of the crawling larvae as descriptors of their motion. By tracking larvae from wild-type strains and models of the Fragile X mental retardation as well as Alzheimer disease, we show these mutants exhibit impaired crawling. We further show that the magnitude of impairment correlates with the severity of the mutation, demonstrating the sensitivity and the dynamic range of the method. Finally, we study larvae with altered expression of the shaggy gene, a homolog of Glycogen Synthase Kinase-3 (GSK-3), which has been implicated in Alzheimer disease. Surprisingly, we find that both increased and decreased expression of dGSK-3 lead to similar larval crawling impairment. These findings have implications for the use of GSK-3 inhibitors recently proposed for Alzheimer treatment.

Due to their short lifespan, rapid division, and ease of genetic manipulation, yeasts are popular model organisms for studying aging in actively dividing cells. To study replicative aging over many cell divisions, individual cells must be continuously separated from their progeny via a laborious manual microdissection procedure. Microfluidics-based soft-lithography devices have recently been used to automate microdissection of the budding yeast Saccharomyces cerevisiae. However, little is known about replicative aging in Schizosaccharomyces pombe, a rod-shaped yeast that divides by binary fission and shares many conserved biological functions with higher eukaryotes. In this report, we develop a versatile multiphoton lithography method that enables rapid fabrication of three-dimensional master structures for polydimethylsiloxane (PDMS)-based microfluidics. We exploit the rapid prototyping capabilities of multiphoton lithography to create and characterize a cell-capture device that is capable of high-resolution microscopic observation of hundreds of individual S. pombe cells. By continuously removing the progeny cells, we demonstrate that cell growth and protein aggregation can be tracked in individual cells for over ~100 h. Thus, the fission yeast lifespan microdissector (FYLM) provides a powerful on-chip microdissection platform that will enable high-throughput studies of aging in rod-shaped cells.

Mapping reads to a reference sequence is a common step when analyzing allele effects in high-throughput sequencing data. The choice of reference is critical because its effect on quantitative sequence analysis is non-negligible. Recent studies suggest aligning to a single standard reference sequence, as is common practice, can lead to an underlying bias depending on the genetic distances of the target sequences from the reference. To avoid this bias, researchers have resorted to using modified reference sequences. Even with this improvement, various limitations and problems remain unsolved, which include reduced mapping ratios, shifts in read mappings and the selection of which variants to include to remove biases. To address these issues, we propose a novel and generic multi-alignment pipeline. Our pipeline integrates the genomic variations from known or suspected founders into separate reference sequences and performs alignments to each one. By mapping reads to multiple reference sequences and merging them afterward, we are able to rescue more reads and diminish the bias caused by using a single common reference. Moreover, the genomic origin of each read is determined and annotated during the merging process, providing a better source of information to assess differential expression than simple allele queries at known variant positions. Using RNA-seq of a diallel cross, we compare our pipeline with the single-reference pipeline and demonstrate our advantages of more aligned reads and a higher percentage of reads with assigned origins. Database URL: http://csbio.unc.edu/CCstatus/index.py?run=Pseudo.

The rapidly reducing cost of bacterial genome sequencing has lead to its routine use in large-scale microbial analysis. Though mapping approaches can be used to find differences relative to the reference, many bacteria are subject to constant evolutionary pressures resulting in events such as the loss and gain of mobile genetic elements, horizontal gene transfer through recombination and genomic rearrangements. De novo assembly is the reconstruction of the underlying genome sequence, an essential step to understanding bacterial genome diversity. Here we present a high-throughput bacterial assembly and improvement pipeline that has been used to generate nearly 20 000 annotated draft genome assemblies in public databases. We demonstrate its performance on a public data set of 9404 genomes. We find all the genes used in multi-locus sequence typing schema present in 99.6 % of assembled genomes. When tested on low-, neutral- and high-GC organisms, more than 94 % of genes were present and completely intact. The pipeline has been proven to be scalable and robust with a wide variety of datasets without requiring human intervention. All of the software is available on GitHub under the GNU GPL open source license. PMID:28348874

We present a hierarchical principle for object recognition and its application to automatically classify developmental stages of C. elegans animals from a population of mixed stages. The object recognition machine consists of four hierarchical layers, each composed of units upon which evaluation functions output a label score, followed by a grouping mechanism that resolves ambiguities in the score by imposing local consistency constraints. Each layer then outputs groups of units, from which the units of the next layer are derived. Using this hierarchical principle, the machine builds up successively more sophisticated representations of the objects to be classified. The algorithm segments large and small objects, decomposes objects into parts, extracts features from these parts, and classifies them by SVM. We are using this system to analyze phenotypic data from C. elegans high-throughputgenetic screens, and our system overcomes a previous bottleneck in image analysis by achieving near real-time scoring of image data. The system is in current use in a functioning C. elegans laboratory and has processed over two hundred thousand images for lab users. PMID:22053146

Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders without any defined uniting pathophysiology. Ca2+ signaling is emerging as a potential node in the genetic architecture of the disorder. We previously reported decreased inositol trisphosphate (IP3)-mediated Ca2+ release from the endoplasmic reticulum in several rare monogenic syndromes highly comorbid with autism – fragile X and tuberous sclerosis types 1 and 2 syndromes. We now extend those findings to a cohort of subjects with sporadic ASD without any known mutations. We developed and applied a highthroughput Fluorometric Imaging Plate Reader (FLIPR) assay to monitor agonist-evoked Ca2+ signals in human primary skin fibroblasts. Our results indicate that IP3 -mediated Ca2+ release from the endoplasmic reticulum in response to activation of purinergic receptors is significantly depressed in subjects with sporadic as well as rare syndromic forms of ASD. We propose that deficits in IP3-mediated Ca2+ signaling represent a convergent hub function shared across the spectrum of autistic disorders – whether caused by rare highly penetrant mutations or sporadic forms – and holds promise as a biomarker for diagnosis and novel drug discovery. PMID:28145469

Time-lapse live cell imaging is a powerful tool for studying signaling network dynamics and complexity and is uniquely suited to single cell studies of response dynamics, noise, and heritable differences. Although conventional imaging formats have the temporal and spatial resolution needed for such studies, they do not provide the simultaneous advantages of cell tracking, experimental throughput, and precise chemical control. This is particularly problematic for system-level studies using non-adherent model organisms such as yeast, where the motion of cells complicates tracking and where large-scale analysis under a variety of genetic and chemical perturbations is desired. We present here a high-throughput microfluidic imaging system capable of tracking single cells over multiple generations in 128 simultaneous experiments with programmable and precise chemical control. High-resolution imaging and robust cell tracking are achieved through immobilization of yeast cells using a combination of mechanical clamping and polymerization in an agarose gel. The channel and valve architecture of our device allows for the formation of a matrix of 128 integrated agarose gel pads, each allowing for an independent imaging experiment with fully programmable medium exchange via diffusion. We demonstrate our system in the combinatorial and quantitative analysis of the yeast pheromone signaling response across 8 genotypes and 16 conditions, and show that lineage-dependent effects contribute to observed variability at stimulation conditions near the critical threshold for cellular decision making.

The nematode C. elegans has emerged as an important model for the study of conserved genetic pathways regulating fat metabolism as it relates to human obesity and its associated pathologies. Several previous methodologies developed for the visualization of C. elegans triglyceride-rich fat stores have proven to be erroneous, highlighting cellular compartments other than lipid droplets. Other methods require specialized equipment, are time-consuming, or yield inconsistent results. We introduce a rapid, reproducible, fixative-based Nile red staining method for the accurate and rapid detection of neutral lipid droplets in C. elegans. A short fixation step in 40% isopropanol makes animals completely permeable to Nile red, which is then used to stain animals. Spectral properties of this lipophilic dye allow it to strongly and selectively fluoresce in the yellow-green spectrum only when in a lipid-rich environment, but not in more polar environments. Thus, lipid droplets can be visualized on a fluorescent microscope equipped with simple GFP imaging capability after only a brief Nile red staining step in isopropanol. The speed, affordability, and reproducibility of this protocol make it ideally suited for highthroughput screens. We also demonstrate a paired method for the biochemical determination of triglycerides and phospholipids using gas chromatography mass-spectrometry. This more rigorous protocol should be used as confirmation of results obtained from the Nile red microscopic lipid determination. We anticipate that these techniques will become new standards in the field of C. elegans metabolic research. PMID:23568026

Recent advances in high-throughput sequencing (HTS) technologies and computing capacity have produced unprecedented amounts of genomic data that have unraveled the genetics of phenotypic variability in several species. However, operating and integrating current software tools for data analysis still require important investments in highly skilled personnel. Developing accurate, efficient and user-friendly software packages for HTS data analysis will lead to a more rapid discovery of genomic elements relevant to medical, agricultural and industrial applications. We therefore developed Next-Generation Sequencing Eclipse Plug-in (NGSEP), a new software tool for integrated, efficient and user-friendly detection of single nucleotide variants (SNVs), indels and copy number variants (CNVs). NGSEP includes modules for read alignment, sorting, merging, functional annotation of variants, filtering and quality statistics. Analysis of sequencing experiments in yeast, rice and human samples shows that NGSEP has superior accuracy and efficiency, compared with currently available packages for variants detection. We also show that only a comprehensive and accurate identification of repeat regions and CNVs allows researchers to properly separate SNVs from differences between copies of repeat elements. We expect that NGSEP will become a strong support tool to empower the analysis of sequencing data in a wide range of research projects on different species.

Ethanol production by microorganisms is an important renewable energy source. Most processes involve fermentation of sugars from plant feedstock, but there is increasing interest in direct ethanol production by photosynthetic organisms. To facilitate this, a high-throughput screening technique for the detection of ethanol is required. Here, a method for the quantitative detection of ethanol in a microdroplet-based platform is described that can be used for screening cyanobacterial strains to identify those with the highest ethanol productivity levels. The detection of ethanol by enzymatic assay was optimized both in bulk and in microdroplets. In parallel, the encapsulation of engineered ethanol-producing cyanobacteria in microdroplets and their growth dynamics in microdroplet reservoirs were demonstrated. The combination of modular microdroplet operations including droplet generation for cyanobacteria encapsulation, droplet re-injection and pico-injection, and laser-induced fluorescence, were used to create this new platform to screen genetically engineered strains of cyanobacteria with different levels of ethanol production. PMID:25878135

Background In modern life science research it is very important to have an efficient management of highthroughput primary lab data. To realise such an efficient management, four main aspects have to be handled: (I) long term storage, (II) security, (III) upload and (IV) retrieval. Findings In this paper we define central requirements for a primary lab data management and discuss aspects of best practices to realise these requirements. As a proof of concept, we introduce a pipeline that has been implemented in order to manage primary lab data at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK). It comprises: (I) a data storage implementation including a Hierarchical Storage Management system, a relational Oracle Database Management System and a BFiler package to store primary lab data and their meta information, (II) the Virtual Private Database (VPD) implementation for the realisation of data security and the LIMS Light application to (III) upload and (IV) retrieve stored primary lab data. Conclusions With the LIMS Light system we have developed a primary data management system which provides an efficient storage system with a Hierarchical Storage Management System and an Oracle relational database. With our VPD Access Control Method we can guarantee the security of the stored primary data. Furthermore the system provides high performance upload and download and efficient retrieval of data. PMID:22005096

The ability to conduct advanced functional genomic studies of the thousands of 38 sequenced bacteria has been hampered by the lack of available tools for making high39 throughput chromosomal manipulations in a systematic manner that can be applied across 40 diverse species. In this work, we highlight the use of synthetic biological tools to 41 assemble custom suicide vectors with reusable and interchangeable DNA parts to 42 facilitate chromosomal modification at designated loci. These constructs enable an array 43 of downstream applications including gene replacement and creation of gene fusions with 44 affinity purification or localization tags. We employed this approach to engineer 45 chromosomal modifications in a bacterium that has previously proven difficult to 46 manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of 47 662 strains. Furthermore, we demonstrate how these modifications can be used for 48 examining metabolic pathways, protein-protein interactions, and protein localization. The 49 ubiquity of suicide constructs in gene replacement throughout biology suggests that this 50 approach can be applied to engineer a broad range of species for a diverse array of 51 systems biological applications and is amenable to high-throughput implementation.

Systematic gene disruption is a direct way to interrogate a fungal genome to functionally characterize the full suite of genes involved in various biological processes. Metarhizium robertsii is extraordinarily versatile, and it is a pathogen of arthropods, a saprophyte and a beneficial colonizer of rhizospheres. Thus, M. robertsii can be used as a representative to simultaneously study several major lifestyles that are not shared by the "model" fungi Saccharomyces cerevisiae and Neurospora crassa; a systematic genetic analysis of M. robertsii will benefit studies in other fungi. In order to systematically disrupt genes in M. robertsii, we developed a high-throughput gene disruption methodology, which includes two technologies. One is the modified OSCAR-based, high-throughput construction of gene disruption plasmids. This technology involves two donor plasmids (pA-Bar-OSCAR with the herbicide resistance genes Bar and pA-Sur-OSCAR with another herbicide resistance gene Sur) and a recipient binary plasmid pPK2-OSCAR-GFP that was produced by replacing the Bar cassette in pPK2-bar-GFP with a ccdB cassette and recombination recognition sites. Using this technology, a gene disruption plasmid can be constructed in one cloning step in two days. The other is a highly efficient gene disruption technology based on homologous recombination using a Ku70 deletion mutant (ΔMrKu70) as the recipient strain. The deletion of MrKu70, a gene encoding a key component involved in nonhomologous end-joining DNA repair in fungi, dramatically increases the gene disruption efficiency. The frequency of disrupting the conidiation-associated gene Cag8 in ΔMrKu70 was 93% compared to 7% in the wild-type strain. Since ΔMrKu70 is not different from the wild-type strain in development, pathogenicity and tolerance to various abiotic stresses, it can be used as a recipient strain for a systematic gene disruption project to characterize the whole suite of genes involved in the biological processes of

Molecular profiling of tumor tissue to detect alterations, such as oncogenic mutations, plays a vital role in determining treatment options in oncology. Hence, there is an increasing need for a robust and high-throughput technology to detect oncogenic hotspot mutations. Although commercial assays are available to detect genetic alterations in single genes, only a limited amount of tissue is often available from patients, requiring multiplexing to allow for simultaneous detection of mutations in many genes using low DNA input. Even though next-generation sequencing (NGS) platforms provide powerful tools for this purpose, they face challenges such as high cost, large DNA input requirement, complex data analysis, and long turnaround times, limiting their use in clinical settings. We report the development of the next generation mutation multi-analyte panel (MUT-MAP), a high-throughput microfluidic, panel for detecting 120 somatic mutations across eleven genes of therapeutic interest (AKT1, BRAF, EGFR, FGFR3, FLT3, HRAS, KIT, KRAS, MET, NRAS, and PIK3CA) using allele-specific PCR (AS-PCR) and Taqman technology. This mutation panel requires as little as 2 ng of high quality DNA from fresh frozen or 100 ng of DNA from formalin-fixed paraffin-embedded (FFPE) tissues. Mutation calls, including an automated data analysis process, have been implemented to run 88 samples per day. Validation of this platform using plasmids showed robust signal and low cross-reactivity in all of the newly added assays and mutation calls in cell line samples were found to be consistent with the Catalogue of Somatic Mutations in Cancer (COSMIC) database allowing for direct comparison of our platform to Sanger sequencing. High correlation with NGS when compared to the SuraSeq500 panel run on the Ion Torrent platform in a FFPE dilution experiment showed assay sensitivity down to 0.45%. This multiplexed mutation panel is a valuable tool for high-throughput biomarker discovery in personalized

Since the publication of a high-throughput DNA sequencing technology based on PCR reaction was carried out in oil emulsions in 2005, high-throughput DNA sequencing platforms have been evolved to a robust technolog